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null | {
"abstract": " The significant halogenation effects on the essential properties of graphene\nare investigated by the first-principles method. The geometric structures,\nelectronic properties, and magnetic configurations are greatly diversified\nunder the various halogen adsorptions. Fluorination, with the strong\nmulti-orbital chemical bondings, can create the buckled graphene structure,\nwhile the other halogenations do not change the planar {\\sigma} bonding in the\npresence of single-orbital hybridization. Electronic structures consist of the\ncarbon-, adatom- and (carbon, adatom)-dominated energy bands. All halogenated\ngraphenes belong to hole-doped metals except that fluorinated systems are\nmiddle-gap semiconductors at sufficiently high concentration. Moreover, the\nmetallic ferromagnetism is revealed in certain adatom distributions. The\nunusual hybridization-induced features are clearly evidenced in many van Hove\nsingularities of the density of states. The structure- and adatom-enriched\nessential properties are compared with the measured results, and potential\napplications are also discussed.\n",
"title": "Diversified essential properties in halogenated graphenes"
} | null | null | null | null | true | null | 19301 | null | Default | null | null |
null | {
"abstract": " We propose an information-theoretic framework to quantify multipartite\ncorrelations in classical and quantum systems, answering questions such as:\nwhat is the amount of seven-partite correlations in a given state of ten\nparticles? We identify measures of genuine multipartite correlations, i.e.\nstatistical dependencies which cannot be ascribed to bipartite correlations,\nsatisfying a set of desirable properties. Inspired by ideas developed in\ncomplexity science, we then introduce the concept of weaving to classify states\nwhich display different correlation patterns, but cannot be distinguished by\ncorrelation measures. The weaving of a state is defined as the weighted sum of\ncorrelations of every order. Weaving measures are good descriptors of the\ncomplexity of correlation structures in multipartite systems.\n",
"title": "Quantifying genuine multipartite correlations and their pattern complexity"
} | null | null | null | null | true | null | 19302 | null | Default | null | null |
null | {
"abstract": " We present a theoretical assessment of the expected temporal rates of change\nof periods ($\\dot{\\Pi}$) for low-mass ($M_{\\star}/M_{\\sun} \\lesssim 0.45$) and\nextremely low-mass (ELM, $M_{\\star}/M_{\\sun} \\lesssim 0.18-0.20$) white-dwarf\nstars, based on fully evolutionary low-mass He-core white dwarf and pre-white\ndwarf models. Our analysis is based on a large set of adiabatic periods of\nradial and nonradial pulsation modes computed on a suite of low-mass He-core\nwhite dwarf and pre-white dwarf models with masses ranging from $0.1554$ to\n$0.4352 M_{\\sun}$. We compute the secular rates of period change of radial\n($\\ell= 0$) and nonradial ($\\ell= 1, 2$) $g$ and $p$ modes for stellar models\nrepresentative of ELMV and pre-ELMV stars, as well as for stellar objects that\nare evolving just before the occurrence of CNO flashes at the early cooling\nbranches. We found that the theoretically expected magnitude of $\\dot{\\Pi}$ of\n$g$ modes for pre-ELMVs are by far larger than for ELMVs. In turn, $\\dot{\\Pi}$\nof $g$ modes for models evolving before the occurrence of CNO flashes are\nlarger than the maximum values of the rates of period change predicted for\npre-ELMV stars. Regarding $p$ and radial modes, we found that the larger\nabsolute values of $\\dot{\\Pi}$ correspond to pre-ELMV models. We conclude that\nany eventual measurement of a rate of period change for a given pulsating\nlow-mass pre-white dwarf or white dwarf star could shed light about its\nevolutionary status. Also, in view of the systematic difficulties in the\nspectroscopic classification of stars of the ELM Survey, an eventual\nmeasurement of $\\dot{\\Pi}$ could help to confirm that a given pulsating star is\nan authentic low-mass white dwarf and not a star from another stellar\npopulation.\n",
"title": "Pulsating low-mass white dwarfs in the frame of new evolutionary sequences: IV. The secular rate of period change"
} | null | null | [
"Physics"
]
| null | true | null | 19303 | null | Validated | null | null |
null | {
"abstract": " The normalized maximum likelihood (NML) is one of the most important\ndistribution in coding theory and statistics. NML is the unique solution (if\nexists) to the pointwise minimax regret problem. However, NML is not defined\neven for simple family of distributions such as the normal distributions. Since\nthere does not exist any meaningful minimax-regret distribution for such case,\nit is pointed out that NML with luckiness (LNML) can be employed as an\nalternative to NML. In this paper, we develop the closed form of LNMLs for\nmultivariate normal distributions.\n",
"title": "Normalized Maximum Likelihood with Luckiness for Multivariate Normal Distributions"
} | null | null | null | null | true | null | 19304 | null | Default | null | null |
null | {
"abstract": " Existing memory management mechanisms used in commodity computing machines\ntypically adopt hardware based address interleaving and OS directed random\nmemory allocation to service generic application requests. These conventional\nmemory management mechanisms are challenged by contention at multiple memory\nlevels, a daunting variety of workload behaviors, and an increasingly\ncomplicated memory hierarchy. Our ISCA-41 paper proposes vertical partitioning\nto eliminate shared resource contention at multiple levels in the memory\nhierarchy. Combined with horizontal memory management policies, our framework\nsupports a flexible policy space for tackling diverse application needs in\nproduction environment and is suitable for future heterogeneous memory systems.\n",
"title": "Tackling Diversity and Heterogeneity by Vertical Memory Management"
} | null | null | [
"Computer Science"
]
| null | true | null | 19305 | null | Validated | null | null |
null | {
"abstract": " The regular icosahedron is connected to many exceptional objects in\nmathematics. Here we describe two constructions of the $\\mathrm{E}_8$ lattice\nfrom the icosahedron. One uses a subring of the quaternions called the\n\"icosians\", while the other uses du Val's work on the resolution of Kleinian\nsingularities. Together they link the golden ratio, the quaternions, the\nquintic equation, the 600-cell, and the Poincare homology 3-sphere. We leave it\nas a challenge to the reader to find the connection between these two\nconstructions.\n",
"title": "From the Icosahedron to E8"
} | null | null | null | null | true | null | 19306 | null | Default | null | null |
null | {
"abstract": " This paper demonstrates the feasibility of implementing Real-Time State\nEstimators (RTSEs) for Active Distribution Networks (ADNs) in\nField-Programmable Gate Arrays (FPGAs) by presenting an operational prototype.\nThe prototype is based on a Linear State Estimator (LSE) that uses\nsynchrophasor measurements from Phasor Measurement Units (PMUs). The underlying\nalgorithm is the Sequential Discrete Kalman Filter (SDKF), an equivalent\nformulation of the Discrete Kalman Filter (DKF) for the case of uncorrelated\nmeasurement noise. In this regard, this work formally proves the equivalence\nthe SDKF and the DKF, and highlights the suitability of the SDKF for an FPGA\nimplementation by means of a computational complexity analysis. The developed\nprototype is validated using a case study adapted from the IEEE 34-node\ndistribution test feeder.\n",
"title": "Sequential Discrete Kalman Filter for Real-Time State Estimation in Power Distribution Systems: Theory and Implementation"
} | null | null | null | null | true | null | 19307 | null | Default | null | null |
null | {
"abstract": " We develop game-theoretic semantics (GTS) for the fragment ATL+ of the full\nAlternating-time Temporal Logic ATL*, essentially extending a recently\nintroduced GTS for ATL. We first show that the new game-theoretic semantics is\nequivalent to the standard semantics of ATL+ (based on perfect recall\nstrategies). We then provide an analysis, based on the new semantics, of the\nmemory and time resources needed for model checking ATL+. Based on that, we\nestablish that strategies that use only a very limited amount of memory suffice\nfor ATL+. Furthermore, using the GTS we provide a new algorithm for model\nchecking of ATL+ and identify a natural hierarchy of tractable fragments of\nATL+ that extend ATL.\n",
"title": "Game-Theoretic Semantics for ATL+ with Applications to Model Checking"
} | null | null | null | null | true | null | 19308 | null | Default | null | null |
null | {
"abstract": " The wide usage of Machine Learning (ML) has lead to research on the attack\nvectors and vulnerability of these systems. The defenses in this area are\nhowever still an open problem, and often lead to an arms race. We define a\nnaive, secure classifier at test time and show that a Gaussian Process (GP) is\nan instance of this classifier given two assumptions: one concerns the\ndistances in the training data, the other rejection at test time. Using these\nassumptions, we are able to show that a classifier is either secure, or\ngeneralizes and thus learns. Our analysis also points towards another factor\ninfluencing robustness, the curvature of the classifier. This connection is not\nunknown for linear models, but GP offer an ideal framework to study this\nrelationship for nonlinear classifiers. We evaluate on five security and two\ncomputer vision datasets applying test and training time attacks and membership\ninference. We show that we only change which attacks are needed to succeed,\ninstead of alleviating the threat. Only for membership inference, there is a\nsetting in which attacks are unsuccessful (<10% increase in accuracy over\nrandom guess). Given these results, we define a classification scheme based on\nvoting, ParGP. This allows us to decide how many points vote and how large the\nagreement on a class has to be. This ensures a classification output only in\ncases when there is evidence for a decision, where evidence is parametrized. We\nevaluate this scheme and obtain promising results.\n",
"title": "Killing Three Birds with one Gaussian Process: Analyzing Attack Vectors on Classification"
} | null | null | null | null | true | null | 19309 | null | Default | null | null |
null | {
"abstract": " We analyse a linear regression problem with nonconvex regularization called\nsmoothly clipped absolute deviation (SCAD) under an overcomplete Gaussian basis\nfor Gaussian random data. We propose an approximate message passing (AMP)\nalgorithm considering nonconvex regularization, namely SCAD-AMP, and\nanalytically show that the stability condition corresponds to the de\nAlmeida--Thouless condition in spin glass literature. Through asymptotic\nanalysis, we show the correspondence between the density evolution of SCAD-AMP\nand the replica symmetric solution. Numerical experiments confirm that for a\nsufficiently large system size, SCAD-AMP achieves the optimal performance\npredicted by the replica method. Through replica analysis, a phase transition\nbetween replica symmetric (RS) and replica symmetry breaking (RSB) region is\nfound in the parameter space of SCAD. The appearance of the RS region for a\nnonconvex penalty is a significant advantage that indicates the region of\nsmooth landscape of the optimization problem. Furthermore, we analytically show\nthat the statistical representation performance of the SCAD penalty is better\nthan that of L1-based methods, and the minimum representation error under RS\nassumption is obtained at the edge of the RS/RSB phase. The correspondence\nbetween the convergence of the existing coordinate descent algorithm and RS/RSB\ntransition is also indicated.\n",
"title": "Approximate message passing for nonconvex sparse regularization with stability and asymptotic analysis"
} | null | null | null | null | true | null | 19310 | null | Default | null | null |
null | {
"abstract": " The topological data analysis method \"concurrence topology\" is applied to\nmutation frequencies in 69 genes in glioblastoma data. In dimension 1 some\napparent \"mutual exclusivity\" is found. By simulation of data having\napproximately the same second order dependence structure as that found in the\ndata, it appears that one triple of mutations, PTEN, RB1, TP53, exhibits mutual\nexclusivity that depends on special features of the third order dependence and\nmay reflect global dependence among a larger group of genes. A bootstrap\nanalysis suggests that this form of mutual exclusivity is not uncommon in the\npopulation from which the data were drawn.\n",
"title": "Concurrence Topology of Some Cancer Genomics Data"
} | null | null | [
"Statistics"
]
| null | true | null | 19311 | null | Validated | null | null |
null | {
"abstract": " As is known, an elementary excitation of a many-particle system with\nboundaries is not characterized by a definite momentum. Here, we obtain the\nformula for the quasimomentum of an elementary excitation for a one-dimensional\nsystem of $N$ spinless point bosons with zero boundary conditions (BCs). We\nalso find that the dispersion law $E(p)$ of the system with zero BCs coincides\nwith that of a system with periodic BCs. The elementary excitations are defined\nwithin a new approach proposed earlier by the author. This approach is\nmathematically equivalent to the traditional approach by Lieb, but differs from\nit by a simpler way of enumeration of excited states and leads to a single\ndispersion law (instead of two ones in the Lieb's approach).\n",
"title": "Quasimomentum of an elementary excitation for a system of point bosons with zero boundary conditions"
} | null | null | null | null | true | null | 19312 | null | Default | null | null |
null | {
"abstract": " In a previous paper [ arXiv:1508.03269 ] we described the techniques we\nsuccessfully employed for automatically reconstructing the whole move sequence\nof a Go game by means of a set of pictures. Now we describe how it is possible\nto reconstruct the move sequence by means of a video stream (which may be\nprovided by an unattended webcam), possibly in real-time. Although the basic\nalgorithms remain the same, we will discuss the new problems that arise when\ndealing with videos, with special care for the ones that could block a\nreal-time analysis and require an improvement of our previous techniques or\neven a completely brand new approach. Eventually we present a number of\npreliminary but positive experimental results supporting the effectiveness of\nthe software we are developing, built on the ideas here outlined.\n",
"title": "Moving to VideoKifu: the last steps toward a fully automatic record-keeping of a Go game"
} | null | null | null | null | true | null | 19313 | null | Default | null | null |
null | {
"abstract": " In this work we introduce malware detection from raw byte sequences as a\nfruitful research area to the larger machine learning community. Building a\nneural network for such a problem presents a number of interesting challenges\nthat have not occurred in tasks such as image processing or NLP. In particular,\nwe note that detection from raw bytes presents a sequence problem with over two\nmillion time steps and a problem where batch normalization appear to hinder the\nlearning process. We present our initial work in building a solution to tackle\nthis problem, which has linear complexity dependence on the sequence length,\nand allows for interpretable sub-regions of the binary to be identified. In\ndoing so we will discuss the many challenges in building a neural network to\nprocess data at this scale, and the methods we used to work around them.\n",
"title": "Malware Detection by Eating a Whole EXE"
} | null | null | null | null | true | null | 19314 | null | Default | null | null |
null | {
"abstract": " In this paper, we investigate the model checking (MC) problem for Halpern and\nShoham's interval temporal logic HS. In the last years, interval temporal logic\nMC has received an increasing attention as a viable alternative to the\ntraditional (point-based) temporal logic MC, which can be recovered as a\nspecial case. Most results have been obtained under the homogeneity assumption,\nthat constrains a proposition letter to hold over an interval if and only if it\nholds over each component state. Recently, Lomuscio and Michaliszyn proposed a\nway to relax such an assumption by exploiting regular expressions to define the\nbehaviour of proposition letters over intervals in terms of their component\nstates. When homogeneity is assumed, the exact complexity of MC is a difficult\nopen question for full HS and for its two syntactically maximal fragments\nAA'BB'E' and AA'EB'E'. In this paper, we provide an asymptotically optimal\nbound to the complexity of these two fragments under the more expressive\nsemantic variant based on regular expressions by showing that their MC problem\nis AEXP_pol-complete, where AEXP_pol denotes the complexity class of problems\ndecided by exponential-time bounded alternating Turing Machines making a\npolynomially bounded number of alternations.\n",
"title": "On the Complexity of Model Checking for Syntactically Maximal Fragments of the Interval Temporal Logic HS with Regular Expressions"
} | null | null | null | null | true | null | 19315 | null | Default | null | null |
null | {
"abstract": " We prove that the moduli space of complete Riemannian metrics of bounded\ngeometry and uniformly positive scalar curvature on an orientable 3-manifold is\npath-connected. This generalizes the main result of the fourth author [Mar12]\nin the compact case. The proof uses Ricci flow with surgery as well as\narguments involving performing infinite connected sums with control on the\ngeometry.\n",
"title": "Deforming 3-manifolds of bounded geometry and uniformly positive scalar curvature"
} | null | null | null | null | true | null | 19316 | null | Default | null | null |
null | {
"abstract": " We consider the problem of optimal dynamic information acquisition from many\ncorrelated information sources. Each period, the decision-maker jointly takes\nan action and allocates a fixed number of observations across the available\nsources. His payoff depends on the actions taken and on an unknown state. In\nthe canonical setting of jointly normal information sources, we show that the\noptimal dynamic information acquisition rule proceeds myopically after finitely\nmany periods. If signals are acquired in large blocks each period, then the\noptimal rule turns out to be myopic from period 1. These results demonstrate\nthe possibility of robust and \"simple\" optimal information acquisition, and\nsimplify the analysis of dynamic information acquisition in a widely used\ninformational environment.\n",
"title": "Optimal and Myopic Information Acquisition"
} | null | null | null | null | true | null | 19317 | null | Default | null | null |
null | {
"abstract": " The celebrated theorem of Robertson and Seymour states that in the family of\nminor-closed graph classes, there is a unique minimal class of graphs of\nunbounded tree-width, namely, the class of planar graphs. In the case of\ntree-width, the restriction to minor-closed classes is justified by the fact\nthat the tree-width of a graph is never smaller than the tree-width of any of\nits minors. This, however, is not the case with respect to clique-width, as the\nclique-width of a graph can be (much) smaller than the clique-width of its\nminor. On the other hand, the clique-width of a graph is never smaller than the\nclique-width of any of its induced subgraphs, which allows us to be restricted\nto hereditary classes (that is, classes closed under taking induced subgraphs),\nwhen we study clique-width. Up to date, only finitely many minimal hereditary\nclasses of graphs of unbounded clique-width have been discovered in the\nliterature. In the present paper, we prove that the family of such classes is\ninfinite. Moreover, we show that the same is true with respect to linear\nclique-width.\n",
"title": "Infinitely many minimal classes of graphs of unbounded clique-width"
} | null | null | null | null | true | null | 19318 | null | Default | null | null |
null | {
"abstract": " In this paper we consider the problem of distributed Nash equilibrium (NE)\nseeking over networks, a setting in which players have limited local\ninformation. We start from a continuous-time gradient-play dynamics that\nconverges to an NE under strict monotonicity of the pseudo-gradient and assumes\nperfect information, i.e., instantaneous all-to-all player communication. We\nconsider how to modify this gradient-play dynamics in the case of partial, or\nnetworked information between players. We propose an augmented gradient-play\ndynamics with correction in which players communicate locally only with their\nneighbours to compute an estimate of the other players' actions. We derive the\nnew dynamics based on the reformulation as a multi-agent coordination problem\nover an undirected graph. We exploit incremental passivity properties and show\nthat a synchronizing, distributed Laplacian feedback can be designed using\nrelative estimates of the neighbours. Under a strict monotonicity property of\nthe pseudo-gradient, we show that the augmented gradient-play dynamics\nconverges to consensus on the NE of the game. We further discuss two cases that\nhighlight the tradeoff between properties of the game and the communication\ngraph.\n",
"title": "A Passivity-Based Approach to Nash Equilibrium Seeking over Networks"
} | null | null | null | null | true | null | 19319 | null | Default | null | null |
null | {
"abstract": " The magnetic, thermodynamic and dielectric properties of the $\\gamma$ -\nFe${_2}$WO${_6}$ system is reported. Crystallizing in the centrosymmetric\n$Pbcn$ space group, this particular polymorph exhibits a number of different\nmagnetic transitions, all of which are seen to exhibit a finite\nmagneto-dielectric coupling. At the lowest measured temperatures, the magnetic\nground state appears to be glass-like, as evidenced by the waiting time\ndependence of the magnetic relaxation. Also reflected in the frequency\ndependent dielectric measurements, these signatures possibly arise as a\nconsequence of the oxygen non-stoichiometry, which promotes an inhomogeneous\nmagnetic and electronic ground state.\n",
"title": "Magnetic and dielectric investigations of $γ$ - Fe${_2}$WO${_6}$"
} | null | null | null | null | true | null | 19320 | null | Default | null | null |
null | {
"abstract": " A classification algorithm, called the Linear Centralization Classifier\n(LCC), is introduced. The algorithm seeks to find a transformation that best\nmaps instances from the feature space to a space where they concentrate towards\nthe center of their own classes, while maximimizing the distance between class\ncenters. We formulate the classifier as a quadratic program with quadratic\nconstraints. We then simplify this formulation to a linear program that can be\nsolved effectively using a linear programming solver (e.g., simplex-dual). We\nextend the formulation for LCC to enable the use of kernel functions for\nnon-linear classification applications. We compare our method with two standard\nclassification methods (support vector machine and linear discriminant\nanalysis) and four state-of-the-art classification methods when they are\napplied to eight standard classification datasets. Our experimental results\nshow that LCC is able to classify instances more accurately (based on the area\nunder the receiver operating characteristic) in comparison to other tested\nmethods on the chosen datasets. We also report the results for LCC with a\nparticular kernel to solve for synthetic non-linear classification problems.\n",
"title": "Linear centralization classifier"
} | null | null | null | null | true | null | 19321 | null | Default | null | null |
null | {
"abstract": " In this paper, we address the problem of spatio-temporal person retrieval\nfrom multiple videos using a natural language query, in which we output a tube\n(i.e., a sequence of bounding boxes) which encloses the person described by the\nquery. For this problem, we introduce a novel dataset consisting of videos\ncontaining people annotated with bounding boxes for each second and with five\nnatural language descriptions. To retrieve the tube of the person described by\na given natural language query, we design a model that combines methods for\nspatio-temporal human detection and multimodal retrieval. We conduct\ncomprehensive experiments to compare a variety of tube and text representations\nand multimodal retrieval methods, and present a strong baseline in this task as\nwell as demonstrate the efficacy of our tube representation and multimodal\nfeature embedding technique. Finally, we demonstrate the versatility of our\nmodel by applying it to two other important tasks.\n",
"title": "Spatio-temporal Person Retrieval via Natural Language Queries"
} | null | null | null | null | true | null | 19322 | null | Default | null | null |
null | {
"abstract": " The formation and the interaction of multiple cavities, induced by tightly\nfocused femtosecond laser pulses, are studied by using a developed numerical\ntool, including the thermo-elasto-plastic material response. Simulations are\nperformed in fused silica in cases of one, two, and four spots of laser energy\ndeposition. The relaxation of the heated matter, launching shock waves in the\nsurrounding cold material, leads to cavity formation and emergence of areas\nwhere cracks may be induced. Results show that the laser-induced structure\nshape depends on the energy deposition configuration and demonstrate the\npotential of the used numerical tool to obtain the desired designed structure\nor technological process.\n",
"title": "Thermo-elasto-plastic simulations of femtosecond laser-induced multiple-cavity in fused silica"
} | null | null | [
"Physics"
]
| null | true | null | 19323 | null | Validated | null | null |
null | {
"abstract": " Machine-learning potentials (MLPs) for atomistic simulations are a promising\nalternative to conventional classical potentials. Current approaches rely on\ndescriptors of the local atomic environment with dimensions that increase\nquadratically with the number of chemical species. In this article, we\ndemonstrate that such a scaling can be avoided in practice. We show that a\nmathematically simple and computationally efficient descriptor with constant\ncomplexity is sufficient to represent transition-metal oxide compositions and\nbiomolecules containing 11 chemical species with a precision of around 3\nmeV/atom. This insight removes a perceived bound on the utility of MLPs and\npaves the way to investigate the physics of previously inaccessible materials\nwith more than ten chemical species.\n",
"title": "Efficient and Accurate Machine-Learning Interpolation of Atomic Energies in Compositions with Many Species"
} | null | null | null | null | true | null | 19324 | null | Default | null | null |
null | {
"abstract": " In this paper we consider a network of processors aiming at cooperatively\nsolving linear programming problems subject to uncertainty. Each node only\nknows a common cost function and its local uncertain constraint set. We propose\na randomized, distributed algorithm working under time-varying, asynchronous\nand directed communication topology. The algorithm is based on a local\ncomputation and communication paradigm. At each communication round, nodes\nperform two updates: (i) a verification in which they check-in a randomized\nsetup-the robust feasibility (and hence optimality) of the candidate optimal\npoint, and (ii) an optimization step in which they exchange their candidate\nbases (minimal sets of active constraints) with neighbors and locally solve an\noptimization problem whose constraint set includes: a sampled constraint\nviolating the candidate optimal point (if it exists), agent's current basis and\nthe collection of neighbor's basis. As main result, we show that if a processor\nsuccessfully performs the verification step for a sufficient number of\ncommunication rounds, it can stop the algorithm since a consensus has been\nreached. The common solution is-with high confidence-feasible (and hence\noptimal) for the entire set of uncertainty except a subset having arbitrary\nsmall probability measure. We show the effectiveness of the proposed\ndistributed algorithm on a multi-core platform in which the nodes communicate\nasynchronously.\n",
"title": "Randomized Constraints Consensus for Distributed Robust Linear Programming"
} | null | null | null | null | true | null | 19325 | null | Default | null | null |
null | {
"abstract": " The low-frequency vibrational and low-temperature thermal properties of\namorphous solids are markedly different from those of crystalline solids. This\nsituation is counter-intuitive because any solid material is expected to behave\nas a homogeneous elastic body in the continuum limit, in which vibrational\nmodes are phonons following the Debye law. A number of phenomenological\nexplanations have been proposed, which assume elastic heterogeneities, soft\nlocalized vibrations, and so on. Recently, the microscopic mean-field theories\nhave been developed to predict the universal non-Debye scaling law. Considering\nthese theoretical arguments, it is absolutely necessary to directly observe the\nnature of the low-frequency vibrations of amorphous solids and determine the\nlaws that such vibrations obey. Here, we perform an extremely large-scale\nvibrational mode analysis of a model amorphous solid. We find that the scaling\nlaw predicted by the mean-field theory is violated at low frequency, and in the\ncontinuum limit, the vibrational modes converge to a mixture of phonon modes\nfollowing the Debye law and soft localized modes following another universal\nnon-Debye scaling law.\n",
"title": "Continuum limit of the vibrational properties of amorphous solids"
} | null | null | null | null | true | null | 19326 | null | Default | null | null |
null | {
"abstract": " This paper deals with the initial value problem for the multi-term fractional\ndifferential equation. The fractional derivative is defined in the Caputo\nsense. Firstly the initial value problem is transformed into a equivalent\nVolterra-type integral equation under appropriate assumptions. Then new\nexistence results for smooth solutions are established by using the Schauder\nfixed point theorem.\n",
"title": "Existence of smooth solutions of multi-term Caputo-type fractional differential equations"
} | null | null | null | null | true | null | 19327 | null | Default | null | null |
null | {
"abstract": " The CEV model subsumes some of the previous option pricing models. An\nimportant parameter in the model is the parameter b, the elasticity of\nvolatility. For b=0, b=-1/2, and b=-1 the CEV model reduces respectively to the\nBSM model, the square-root model of Cox and Ross, and the Bachelier model. Both\nin the case of the BSM model and in the case of the CEV model it has become\ntraditional to begin a discussion of option pricing by starting with the\nvanilla European calls and puts. In the case of BSM model simpler solutions are\nthe log and power solutions. These contracts, despite the simplicity of their\nmathematical description, are attracting increasing attention as a trading\ninstrument. Similar simple solutions have not been studied so far in a\nsystematic fashion for the CEV model. We use Kovacic's algorithm to derive, for\nall half-integer values of b, all solutions \"in quadratures\" of the CEV\nordinary differential equation. These solutions give rise, by separation of\nvariables, to simple solutions to the CEV partial differential equation. In\nparticular, when b=...,-5/2,-2,-3/2,-1, 1, 3/2, 2, 5/2,..., we obtain four\nclasses of denumerably infinite elementary function solutions, when b=-1/2 and\nb=1/2 we obtain two classes of denumerably infinite elementary function\nsolutions, whereas, when b=0 we find two elementary function solutions. In the\nderived solutions we have also dispensed with the unnecessary assumption made\nin the the BSM model asserting that the underlying asset pays no dividends\nduring the life of the option.\n",
"title": "Classes of elementary function solutions to the CEV model. I"
} | null | null | [
"Quantitative Finance"
]
| null | true | null | 19328 | null | Validated | null | null |
null | {
"abstract": " Classical results of Chentsov and Campbell state that -- up to constant\nmultiples -- the only $2$-tensor field of a statistical model which is\ninvariant under congruent Markov morphisms is the Fisher metric and the only\ninvariant $3$-tensor field is the Amari-Chentsov tensor. We generalize this\nresult for arbitrary degree $n$, showing that any family of $n$-tensors which\nis invariant under congruent Markov morphisms is algebraically generated by the\ncanonical tensor fields defined in an earlier paper.\n",
"title": "Congruent families and invariant tensors"
} | null | null | null | null | true | null | 19329 | null | Default | null | null |
null | {
"abstract": " Smartphones have become the most pervasive devices in people's lives, and are\nclearly transforming the way we live and perceive technology. Today's\nsmartphones benefit from almost ubiquitous Internet connectivity and come\nequipped with a plethora of inexpensive yet powerful embedded sensors, such as\naccelerometer, gyroscope, microphone, and camera. This unique combination has\nenabled revolutionary applications based on the mobile crowdsensing paradigm,\nsuch as real-time road traffic monitoring, air and noise pollution, crime\ncontrol, and wildlife monitoring, just to name a few. Differently from prior\nsensing paradigms, humans are now the primary actors of the sensing process,\nsince they become fundamental in retrieving reliable and up-to-date information\nabout the event being monitored. As humans may behave unreliably or\nmaliciously, assessing and guaranteeing Quality of Information (QoI) becomes\nmore important than ever. In this paper, we provide a new framework for\ndefining and enforcing the QoI in mobile crowdsensing, and analyze in depth the\ncurrent state-of-the-art on the topic. We also outline novel research\nchallenges, along with possible directions of future work.\n",
"title": "Quality of Information in Mobile Crowdsensing: Survey and Research Challenges"
} | null | null | null | null | true | null | 19330 | null | Default | null | null |
null | {
"abstract": " Blockchain, which is a technology for distributedly managing ledger\ninformation over multiple nodes without a centralized system, has elicited\nincreasing attention. Performing experiments on actual blockchains are\ndifficult because a large number of nodes in wide areas are necessary. In this\nstudy, we developed a blockchain network simulator SimBlock for such\nexperiments. Unlike the existing simulators, SimBlock can easily change\nbehavior of node, so that it enables to investigate the influence of nodes'\nbehavior on blockchains. We compared some simulation results with the measured\nvalues in actual blockchains to demonstrate the validity of this simulator.\nFurthermore, to show practical usage, we conducted two experiments which\nclarify the influence of neighbor node selection algorithms and relay networks\non the block propagation time. The simulator could depict the effects of the\ntwo techniques on block propagation time. The simulator will be publicly\navailable in a few months.\n",
"title": "SimBlock: A Blockchain Network Simulator"
} | null | null | null | null | true | null | 19331 | null | Default | null | null |
null | {
"abstract": " We propose a multinomial logistic regression model for link prediction in a\ntime series of directed binary networks. To account for the dynamic nature of\nthe data we employ a dynamic model for the model parameters that is strongly\nconnected with the fused lasso penalty. In addition to promoting sparseness,\nthis prior allows us to explore the presence of change points in the structure\nof the network. We introduce fast computational algorithms for estimation and\nprediction using both optimization and Bayesian approaches. The performance of\nthe model is illustrated using simulated data and data from a financial trading\nnetwork in the NYMEX natural gas futures market. Supplementary material\ncontaining the trading network data set and code to implement the algorithms is\navailable online.\n",
"title": "Bayesian Fused Lasso regression for dynamic binary networks"
} | null | null | null | null | true | null | 19332 | null | Default | null | null |
null | {
"abstract": " Traditionally, kernel learning methods requires positive definitiveness on\nthe kernel, which is too strict and excludes many sophisticated similarities,\nthat are indefinite, in multimedia area. To utilize those indefinite kernels,\nindefinite learning methods are of great interests. This paper aims at the\nextension of the logistic regression from positive semi-definite kernels to\nindefinite kernels. The model, called indefinite kernel logistic regression\n(IKLR), keeps consistency to the regular KLR in formulation but it essentially\nbecomes non-convex. Thanks to the positive decomposition of an indefinite\nmatrix, IKLR can be transformed into a difference of two convex models, which\nfollows the use of concave-convex procedure. Moreover, we employ an inexact\nsolving scheme to speed up the sub-problem and develop a concave-inexact-convex\nprocedure (CCICP) algorithm with theoretical convergence analysis. Systematical\nexperiments on multi-modal datasets demonstrate the superiority of the proposed\nIKLR method over kernel logistic regression with positive definite kernels and\nother state-of-the-art indefinite learning based algorithms.\n",
"title": "Indefinite Kernel Logistic Regression"
} | null | null | null | null | true | null | 19333 | null | Default | null | null |
null | {
"abstract": " Dense suspensions are non-Newtonian fluids which exhibit strong shear\nthickening and normal stress differences. Using numerical simulation of\nextensional and shear flows, we investigate how rheological properties are\ndetermined by the microstructure which is built under flows and by the\ninteractions between particles. By imposing extensional and shear flows, we can\nassess the degree of flow-type dependence in regimes below and above\nthickening. Even when the flow-type dependence is hindered, nondissipative\nresponses, such as normal stress differences, are present and characterise the\nnon-Newtonian behaviour of dense suspensions.\n",
"title": "Microstructure and thickening of dense suspensions under extensional and shear flows"
} | null | null | null | null | true | null | 19334 | null | Default | null | null |
null | {
"abstract": " One of the open challenges in designing robots that operate successfully in\nthe unpredictable human environment is how to make them able to predict what\nactions they can perform on objects, and what their effects will be, i.e., the\nability to perceive object affordances. Since modeling all the possible world\ninteractions is unfeasible, learning from experience is required, posing the\nchallenge of collecting a large amount of experiences (i.e., training data).\nTypically, a manipulative robot operates on external objects by using its own\nhands (or similar end-effectors), but in some cases the use of tools may be\ndesirable, nevertheless, it is reasonable to assume that while a robot can\ncollect many sensorimotor experiences using its own hands, this cannot happen\nfor all possible human-made tools.\nTherefore, in this paper we investigate the developmental transition from\nhand to tool affordances: what sensorimotor skills that a robot has acquired\nwith its bare hands can be employed for tool use? By employing a visual and\nmotor imagination mechanism to represent different hand postures compactly, we\npropose a probabilistic model to learn hand affordances, and we show how this\nmodel can generalize to estimate the affordances of previously unseen tools,\nultimately supporting planning, decision-making and tool selection tasks in\nhumanoid robots. We present experimental results with the iCub humanoid robot,\nand we publicly release the collected sensorimotor data in the form of a hand\nposture affordances dataset.\n",
"title": "Learning at the Ends: From Hand to Tool Affordances in Humanoid Robots"
} | null | null | [
"Computer Science",
"Statistics"
]
| null | true | null | 19335 | null | Validated | null | null |
null | {
"abstract": " We study rewriting for equational theories in the context of symmetric\nmonoidal categories where there is a separable Frobenius monoid on each object.\nThese categories, also called hypergraph categories, are increasingly relevant:\nFrobenius structures recently appeared in cross-disciplinary applications,\nincluding the study of quantum processes, dynamical systems and natural\nlanguage processing. In this work we give a combinatorial characterisation of\narrows of a free hypergraph category as cospans of labelled hypergraphs and\nestablish a precise correspondence between rewriting modulo Frobenius structure\non the one hand and double-pushout rewriting of hypergraphs on the other. This\ninterpretation allows to use results on hypergraphs to ensure decidability of\nconfluence for rewriting in a free hypergraph category. Our results generalise\nprevious approaches where only categories generated by a single object (props)\nwere considered.\n",
"title": "Rewriting in Free Hypergraph Categories"
} | null | null | null | null | true | null | 19336 | null | Default | null | null |
null | {
"abstract": " In this work we addressed the issue of applying a stochastic classifier and a\nlocal, fuzzy confusion matrix under the framework of multi-label\nclassification. We proposed a novel solution to the problem of correcting label\npairwise ensembles. The main step of the correction procedure is to compute\nclassifier-specific competence and cross-competence measures, which estimates\nerror pattern of the underlying classifier. At the fusion phase we employed two\nweighting approaches based on information theory. The classifier weights\npromote base classifiers which are the most susceptible to the correction based\non the fuzzy confusion matrix. During the experimental study, the proposed\napproach was compared against two reference methods. The comparison was made in\nterms of six different quality criteria. The conducted experiments reveals that\nthe proposed approach eliminates one of main drawbacks of the original\nFCM-based approach i.e. the original approach is vulnerable to the imbalanced\nclass/label distribution. What is more, the obtained results shows that the\nintroduced method achieves satisfying classification quality under all\nconsidered quality criteria. Additionally, the impact of fluctuations of data\nset characteristics is reduced.\n",
"title": "Weighting Scheme for a Pairwise Multi-label Classifier Based on the Fuzzy Confusion Matrix"
} | null | null | null | null | true | null | 19337 | null | Default | null | null |
null | {
"abstract": " Wilcoxon Rank-based tests are distribution-free alternatives to the popular\ntwo-sample and paired t-tests. For independent data, they are available in\nseveral R packages such as stats and coin. For clustered data, in spite of the\nrecent methodological developments, there did not exist an R package that makes\nthem available at one place. We present a package clusrank where the latest\ndevelopments are implemented and wrapped under a unified user-friendly\ninterface. With different methods dispatched based on the inputs, this package\noffers great flexibility in rank-based tests for various clustered data. Exact\ntests based on permutations are also provided for some methods. Details of the\nmajor schools of different methods are briefly reviewed. Usages of the package\nclusrank are illustrated with simulated data as well as a real dataset from an\nophthalmological study. The package also enables convenient comparison between\nselected methods under settings that have not been studied before and the\nresults are discussed.\n",
"title": "Wilcoxon Rank-Based Tests for Clustered Data with R Package clusrank"
} | null | null | null | null | true | null | 19338 | null | Default | null | null |
null | {
"abstract": " We propose a method for simultaneously detecting shared and unshared\ncommunities in heterogeneous multilayer weighted and undirected networks. The\nmultilayer network is assumed to follow a generative probabilistic model that\ntakes into account the similarities and dissimilarities between the\ncommunities. We make use of a variational Bayes approach for jointly inferring\nthe shared and unshared hidden communities from multilayer network\nobservations. We show the robustness of our approach compared to state-of-the\nart algorithms in detecting disparate (shared and private) communities on\nsynthetic data as well as on real genome-wide fibroblast proliferation dataset.\n",
"title": "Latent heterogeneous multilayer community detection"
} | null | null | [
"Computer Science",
"Statistics"
]
| null | true | null | 19339 | null | Validated | null | null |
null | {
"abstract": " In this paper, we analyze the behavior of the multivariate symmetric\nuncertainty (MSU) measure through the use of statistical simulation techniques\nunder various mixes of informative and non-informative randomly generated\nfeatures. Experiments show how the number of attributes, their cardinalities,\nand the sample size affect the MSU. We discovered a condition that preserves\ngood quality in the MSU under different combinations of these three factors,\nproviding a new useful criterion to help drive the process of dimension\nreduction.\n",
"title": "Understanding a Version of Multivariate Symmetric Uncertainty to assist in Feature Selection"
} | null | null | [
"Computer Science",
"Statistics"
]
| null | true | null | 19340 | null | Validated | null | null |
null | {
"abstract": " We describe the approximation of a continuous dynamical system on a p. l.\nmanifold or Cantor set by a tractable system. A system is tractable when it has\na finite number of chain components and, with respect to a given full\nbackground measure, almost every point is generic for one of a finite number of\nergodic invariant measures with non-overlapping supports. The approximations\nuse non-degenerate simplicial dynamical systems for p. l. manifolds and\nshift-like dynamical systems for Cantor Sets.\n",
"title": "Approximation Dynamics"
} | null | null | null | null | true | null | 19341 | null | Default | null | null |
null | {
"abstract": " The Wasserstein distance between two probability measures on a metric space\nis a measure of closeness with applications in statistics, probability, and\nmachine learning. In this work, we consider the fundamental question of how\nquickly the empirical measure obtained from $n$ independent samples from $\\mu$\napproaches $\\mu$ in the Wasserstein distance of any order. We prove sharp\nasymptotic and finite-sample results for this rate of convergence for general\nmeasures on general compact metric spaces. Our finite-sample results show the\nexistence of multi-scale behavior, where measures can exhibit radically\ndifferent rates of convergence as $n$ grows.\n",
"title": "Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein distance"
} | null | null | null | null | true | null | 19342 | null | Default | null | null |
null | {
"abstract": " Several recent works have proposed and implemented cryptography as a means to\npreserve privacy and security of patients health data. Nevertheless, the\nweakest point of electronic health record (EHR) systems that relied on these\ncryptographic schemes is key management. Thus, this paper presents the\ndevelopment of privacy and security system for cryptography-based-EHR by taking\nadvantage of the uniqueness of fingerprint and iris characteristic features to\nsecure cryptographic keys in a bio-cryptography framework. The results of the\nsystem evaluation showed significant improvements in terms of time efficiency\nof this approach to cryptographic-based-EHR. Both the fuzzy vault and fuzzy\ncommitment demonstrated false acceptance rate (FAR) of 0%, which reduces the\nlikelihood of imposters gaining successful access to the keys protecting\npatients protected health information. This result also justifies the\nfeasibility of implementing fuzzy key binding scheme in real applications,\nespecially fuzzy vault which demonstrated a better performance during key\nreconstruction.\n",
"title": "Ensuring patients privacy in a cryptographic-based-electronic health records using bio-cryptography"
} | null | null | null | null | true | null | 19343 | null | Default | null | null |
null | {
"abstract": " A proof of concept for high speed near-field imaging with sub-wavelength\nresolution using SLM is presented. An 8 channel THz detector array antenna with\nan electrode gap of 100 um and length of 5 mm is fabricated using the\ncommercially available GaAs semiconductor substrate. Each array antenna can be\nexcited simultaneously by spatially reconfiguring the optical probe beam and\nthe THz electric field can be recorded using 8 channel lock-in amplifiers. By\nscanning the probe beam along the length of the array antenna, a 2D image can\nbe obtained with amplitude, phase and frequency information.\n",
"title": "A Dynamically Reconfigurable Terahertz Array Antenna for Near-field Imaging Applications"
} | null | null | null | null | true | null | 19344 | null | Default | null | null |
null | {
"abstract": " We introduce the notion of stationary actions in the context of C*-algebras.\nWe develop the basics of the theory, and provide applications to several\nergodic theoretical and operator algebraic rigidity problems.\n",
"title": "Stationary C*-dynamical systems"
} | null | null | null | null | true | null | 19345 | null | Default | null | null |
null | {
"abstract": " In supervised machine learning for author name disambiguation, negative\ntraining data are often dominantly larger than positive training data. This\npaper examines how the ratios of negative to positive training data can affect\nthe performance of machine learning algorithms to disambiguate author names in\nbibliographic records. On multiple labeled datasets, three classifiers -\nLogistic Regression, Naïve Bayes, and Random Forest - are trained through\nrepresentative features such as coauthor names, and title words extracted from\nthe same training data but with various positive-negative training data ratios.\nResults show that increasing negative training data can improve disambiguation\nperformance but with a few percent of performance gains and sometimes degrade\nit. Logistic Regression and Naïve Bayes learn optimal disambiguation models\neven with a base ratio (1:1) of positive and negative training data. Also, the\nperformance improvement by Random Forest tends to quickly saturate roughly\nafter 1:10 ~ 1:15. These findings imply that contrary to the common practice\nusing all training data, name disambiguation algorithms can be trained using\npart of negative training data without degrading much disambiguation\nperformance while increasing computational efficiency. This study calls for\nmore attention from author name disambiguation scholars to methods for machine\nlearning from imbalanced data.\n",
"title": "The impact of imbalanced training data on machine learning for author name disambiguation"
} | null | null | null | null | true | null | 19346 | null | Default | null | null |
null | {
"abstract": " Recent successes in word embedding and document embedding have motivated\nresearchers to explore similar representations for networks and to use such\nrepresentations for tasks such as edge prediction, node label prediction, and\ncommunity detection. Such network embedding methods are largely focused on\nfinding distributed representations for unsigned networks and are unable to\ndiscover embeddings that respect polarities inherent in edges. We propose\nSIGNet, a fast scalable embedding method suitable for signed networks. Our\nproposed objective function aims to carefully model the social structure\nimplicit in signed networks by reinforcing the principles of social balance\ntheory. Our method builds upon the traditional word2vec family of embedding\napproaches and adds a new targeted node sampling strategy to maintain\nstructural balance in higher-order neighborhoods. We demonstrate the\nsuperiority of SIGNet over state-of-the-art methods proposed for both signed\nand unsigned networks on several real world datasets from different domains. In\nparticular, SIGNet offers an approach to generate a richer vocabulary of\nfeatures of signed networks to support representation and reasoning.\n",
"title": "SIGNet: Scalable Embeddings for Signed Networks"
} | null | null | null | null | true | null | 19347 | null | Default | null | null |
null | {
"abstract": " The present online social media platform is afflicted with several issues,\nwith hate speech being on the predominant forefront. The prevalence of online\nhate speech has fueled horrific real-world hate-crime such as the mass-genocide\nof Rohingya Muslims, communal violence in Colombo and the recent massacre in\nthe Pittsburgh synagogue. Consequently, It is imperative to understand the\ndiffusion of such hateful content in an online setting. We conduct the first\nstudy that analyses the flow and dynamics of posts generated by hateful and\nnon-hateful users on Gab (gab.com) over a massive dataset of 341K users and 21M\nposts. Our observations confirms that hateful content diffuse farther, wider\nand faster and have a greater outreach than those of non-hateful users. A\ndeeper inspection into the profiles and network of hateful and non-hateful\nusers reveals that the former are more influential, popular and cohesive. Thus,\nour research explores the interesting facets of diffusion dynamics of hateful\nusers and broadens our understanding of hate speech in the online world.\n",
"title": "Spread of hate speech in online social media"
} | null | null | null | null | true | null | 19348 | null | Default | null | null |
null | {
"abstract": " Designing adaptive classifiers for an evolving data stream is a challenging\ntask due to the data size and its dynamically changing nature. Combining\nindividual classifiers in an online setting, the ensemble approach, is a\nwell-known solution. It is possible that a subset of classifiers in the\nensemble outperforms others in a time-varying fashion. However, optimum weight\nassignment for component classifiers is a problem which is not yet fully\naddressed in online evolving environments. We propose a novel data stream\nensemble classifier, called Geometrically Optimum and Online-Weighted Ensemble\n(GOOWE), which assigns optimum weights to the component classifiers using a\nsliding window containing the most recent data instances. We map vote scores of\nindividual classifiers and true class labels into a spatial environment. Based\non the Euclidean distance between vote scores and ideal-points, and using the\nlinear least squares (LSQ) solution, we present a novel, dynamic, and online\nweighting approach. While LSQ is used for batch mode ensemble classifiers, it\nis the first time that we adapt and use it for online environments by providing\na spatial modeling of online ensembles. In order to show the robustness of the\nproposed algorithm, we use real-world datasets and synthetic data generators\nusing the MOA libraries. First, we analyze the impact of our weighting system\non prediction accuracy through two scenarios. Second, we compare GOOWE with 8\nstate-of-the-art ensemble classifiers in a comprehensive experimental\nenvironment. Our experiments show that GOOWE provides improved reactions to\ndifferent types of concept drift compared to our baselines. The statistical\ntests indicate a significant improvement in accuracy, with conservative time\nand memory requirements.\n",
"title": "GOOWE: Geometrically Optimum and Online-Weighted Ensemble Classifier for Evolving Data Streams"
} | null | null | null | null | true | null | 19349 | null | Default | null | null |
null | {
"abstract": " This paper aims to establish theoretical foundations of graph product\nmultilayer networks (GPMNs), a family of multilayer networks that can be\nobtained as a graph product of two or more factor networks. Cartesian, direct\n(tensor), and strong product operators are considered, and then generalized. We\nfirst describe mathematical relationships between GPMNs and their factor\nnetworks regarding their degree/strength, adjacency, and Laplacian spectra, and\nthen show that those relationships can still hold for nonsimple and generalized\nGPMNs. Applications of GPMNs are discussed in three areas: predicting epidemic\nthresholds, modeling propagation in nontrivial space and time, and analyzing\nhigher-order properties of self-similar networks. Directions of future research\nare also discussed.\n",
"title": "Graph Product Multilayer Networks: Spectral Properties and Applications"
} | null | null | null | null | true | null | 19350 | null | Default | null | null |
null | {
"abstract": " A variety of complex systems exhibit different types of relationships\nsimultaneously that can be modeled by multiplex networks. A typical problem is\nto determine the community structure of such systems that, in general, depend\non one or more parameters to be tuned. In this study we propose one measure,\ngrounded on information theory, to find the optimal value of the relax rate\ncharacterizing Multiplex Infomap, the generalization of the Infomap algorithm\nto the realm of multilayer networks. We evaluate our methodology on synthetic\nnetworks, to show that the most representative community structure can be\nreliably identified when the most appropriate relax rate is used. Capitalizing\non these results, we use this measure to identify the most reliable meso-scale\nfunctional organization in the human protein-protein interaction multiplex\nnetwork and compare the observed clusters against a collection of independently\nannotated gene sets from the Molecular Signatures Database (MSigDB). Our\nanalysis reveals that modules obtained with the optimal value of the relax rate\nare biologically significant and, remarkably, with higher functional content\nthan the ones obtained from the aggregate representation of the human proteome.\nOur framework allows us to characterize the meso-scale structure of those\nmultilayer systems whose layers are not explicitly interconnected each other --\nas in the case of edge-colored models -- the ones describing most biological\nnetworks, from proteomes to connectomes.\n",
"title": "Multilayer flows in molecular networks identify biological modules in the human proteome"
} | null | null | null | null | true | null | 19351 | null | Default | null | null |
null | {
"abstract": " Controlling Chaos could be a big factor in getting great stable amounts of\nenergy out of small amounts of not necessarily stable resources. By definition,\nChaos is getting huge changes in the system's output due to unpredictable small\nchanges in initial conditions, and that means we could take advantage of this\nfact and select the proper control system to manipulate system's initial\nconditions and inputs in general and get a desirable output out of otherwise a\nChaotic system. That was accomplished by first building some known chaotic\ncircuit (Chua circuit) and the NI's MultiSim was used to simulate the ANN\ncontrol system. It was shown that this technique can also be used to stabilize\nsome hard to stabilize electronic systems.\n",
"title": "Using Artificial Neural Networks (ANN) to Control Chaos"
} | null | null | [
"Computer Science",
"Physics"
]
| null | true | null | 19352 | null | Validated | null | null |
null | {
"abstract": " We investigate relaxation in the recently discovered \"fracton\" models and\ndiscover that these models naturally host glassy quantum dynamics in the\nabsence of quenched disorder. We begin with a discussion of \"type I\" fracton\nmodels, in the taxonomy of Vijay, Haah, and Fu. We demonstrate that in these\nsystems, the mobility of charges is suppressed exponentially in the inverse\ntemperature. We further demonstrate that when a zero temperature type I fracton\nmodel is placed in contact with a finite temperature heat bath, the approach to\nequilibrium is a logarithmic function of time over an exponentially wide window\nof time scales. Generalizing to the more complex \"type II\" fracton models, we\nfind that the charges exhibit subdiffusion upto a relaxation time that diverges\nat low temperatures as a super-exponential function of inverse temperature.\nThis behaviour is reminiscent of \"nearly localized\" disordered systems, but\noccurs with a translation invariant three-dimensional Hamiltonian. We also\nconjecture that fracton models with conserved charge may support a phase which\nis a thermal metal but a charge insulator.\n",
"title": "Glassy quantum dynamics in translation invariant fracton models"
} | null | null | [
"Physics"
]
| null | true | null | 19353 | null | Validated | null | null |
null | {
"abstract": " A saliency guided hierarchical visual tracking (SHT) algorithm containing\nglobal and local search phases is proposed in this paper. In global search, a\ntop-down saliency model is novelly developed to handle abrupt motion and\nappearance variation problems. Nineteen feature maps are extracted first and\ncombined with online learnt weights to produce the final saliency map and\nestimated target locations. After the evaluation of integration mechanism, the\noptimum candidate patch is passed to the local search. In local search, a\nsuperpixel based HSV histogram matching is performed jointly with an L2-RLS\ntracker to take both color distribution and holistic appearance feature of the\nobject into consideration. Furthermore, a linear refinement search process with\nfast iterative solver is implemented to attenuate the possible negative\ninfluence of dominant particles. Both qualitative and quantitative experiments\nare conducted on a series of challenging image sequences. The superior\nperformance of the proposed method over other state-of-the-art algorithms is\ndemonstrated by comparative study.\n",
"title": "Saliency Guided Hierarchical Robust Visual Tracking"
} | null | null | null | null | true | null | 19354 | null | Default | null | null |
null | {
"abstract": " The present study shows that the performance of CNN is not significantly\ndifferent from the best classical methods and human doctors for classifying\nmediastinal lymph node metastasis of NSCLC from PET/CT images. Because CNN does\nnot need tumor segmentation or feature calculation, it is more convenient and\nmore objective than the classical methods. However, CNN does not make use of\nthe import diagnostic features, which have been proved more discriminative than\nthe texture features for classifying small-sized lymph nodes. Therefore,\nincorporating the diagnostic features into CNN is a promising direction for\nfuture research.\n",
"title": "Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18F-FDG PET/CT images"
} | null | null | null | null | true | null | 19355 | null | Default | null | null |
null | {
"abstract": " This article develops a novel operational semantics for probabilistic\ncontrol-flow graphs (pCFGs) of probabilistic imperative programs with random\nassignment and \"observe\" (or conditioning) statements. The semantics transforms\nprobability distributions (on stores) as control moves from one node to another\nin pCFGs. We relate this semantics to a standard, expectation-transforming,\ndenotational semantics of structured probabilistic imperative programs, by\ntranslating structured programs into (unstructured) pCFGs, and proving adequacy\nof the translation. This shows that the operational semantics can be used\nwithout loss of information, and is faithful to the \"intended\" semantics and\nhence can be used to reason about, for example, the correctness of\ntransformations (as we do in a companion article).\n",
"title": "A Semantics for Probabilistic Control-Flow Graphs"
} | null | null | null | null | true | null | 19356 | null | Default | null | null |
null | {
"abstract": " We provide a compact and unified treatment of power spectrum observables for\nthe effective field theory (EFT) of inflation with the complete set of\noperators that lead to second-order equations of motion in metric perturbations\nin both space and time derivatives, including Horndeski and GLPV theories. We\nrelate the EFT operators in ADM form to the four additional free functions of\ntime in the scalar and tensor equations. Using the generalized slow roll\nformalism, we show that each power spectrum can be described by an integral\nover a single source that is a function of its respective sound horizon. With\nthis correspondence, existing model independent constraints on the source\nfunction can be simply reinterpreted in the more general inflationary context.\nBy expanding these sources around an optimized freeze-out epoch, we also\nprovide characterizations of these spectra in terms of five slow-roll\nhierarchies whose leading order forms are compact and accurate as long as EFT\ncoefficients vary only on timescales greater than an efold. We also clarify the\nrelationship between the unitary gauge observables employed in the EFT and the\ncomoving gauge observables of the post-inflationary universe.\n",
"title": "Generalized Slow Roll in the Unified Effective Field Theory of Inflation"
} | null | null | null | null | true | null | 19357 | null | Default | null | null |
null | {
"abstract": " The magnetic anisotropy (MA) of Mo/Au/Co0.9Fe0.1/Au/MgO(0.7 - 3\nnm)/Au/Co0.9Fe0.1/Au heterostructure has been investigated at room temperature\nas a function of MgO layer thickness (tMgO). Our studies show that while the MA\nof the top layer does not change its character upon variation of tMgO, the\nuniaxial out-of-plane MA of the bottom one undergoes a spin reorientation\ntransition at tMgO of about 0.8 nm, switching to the regime where the\ncoexistence of in- and out-of-plane magnetization alignments is observed. The\nmagnitudes of the magnetic anisotropy constants have been determined from\nferromagnetic resonance and dc-magnetometry measurements. The origin of MA\nevolution has been attributed to a presence of an interlayer exchange coupling\n(IEC) between Co0.9Fe0.1 layers through the thin MgO film.\n",
"title": "MgO thickness-induced spin reorientation transition in Co0.9Fe0.1/MgO/Co0.9Fe0.1 structure"
} | null | null | null | null | true | null | 19358 | null | Default | null | null |
null | {
"abstract": " Ionic solutions are often regarded as fully dissociated ions dispersed in a\npolar solvent. While this picture holds for dilute solutions, at higher ionic\nconcentrations, oppositely charged ions can associate into dimers, referred to\nas Bjerrum pairs. We consider the formation of such pairs within the nonlinear\nPoisson-Boltzmann framework, and investigate their effects on bulk and\ninterfacial properties of electrolytes. Our findings show that pairs can reduce\nthe magnitude of the dielectric decrement of ionic solutions as the ionic\nconcentration increases. We describe the effect of pairs on the Debye screening\nlength, and relate our results to recent surface-force experiments.\nFurthermore, we show that Bjerrum pairs reduce the ionic concentration in bulk\nelectrolyte and at the proximity of charged surfaces, while they enhance the\nattraction between oppositely charged surfaces.\n",
"title": "Bjerrum Pairs in Ionic Solutions: a Poisson-Boltzmann Approach"
} | null | null | null | null | true | null | 19359 | null | Default | null | null |
null | {
"abstract": " Network embedding methodologies, which learn a distributed vector\nrepresentation for each vertex in a network, have attracted considerable\ninterest in recent years. Existing works have demonstrated that vertex\nrepresentation learned through an embedding method provides superior\nperformance in many real-world applications, such as node classification, link\nprediction, and community detection. However, most of the existing methods for\nnetwork embedding only utilize topological information of a vertex, ignoring a\nrich set of nodal attributes (such as, user profiles of an online social\nnetwork, or textual contents of a citation network), which is abundant in all\nreal-life networks. A joint network embedding that takes into account both\nattributional and relational information entails a complete network information\nand could further enrich the learned vector representations. In this work, we\npresent Neural-Brane, a novel Neural Bayesian Personalized Ranking based\nAttributed Network Embedding. For a given network, Neural-Brane extracts latent\nfeature representation of its vertices using a designed neural network model\nthat unifies network topological information and nodal attributes; Besides, it\nutilizes Bayesian personalized ranking objective, which exploits the proximity\nordering between a similar node-pair and a dissimilar node-pair. We evaluate\nthe quality of vertex embedding produced by Neural-Brane by solving the node\nclassification and clustering tasks on four real-world datasets. Experimental\nresults demonstrate the superiority of our proposed method over the\nstate-of-the-art existing methods.\n",
"title": "Neural-Brane: Neural Bayesian Personalized Ranking for Attributed Network Embedding"
} | null | null | null | null | true | null | 19360 | null | Default | null | null |
null | {
"abstract": " In this paper, we continue to study pairwise ($k$-semi-)stratifiable\nbitopological spaces. Some new characterizations of pairwise\n$k$-semi-stratifiable bitopological spaces are provided. Relationships between\npairwise stratifiable and pairwise $k$-semi-stratifiable bitopological spaces\nare further investigated, and an open question recently posed by Li and Lin in\n\\cite{LL} is completely solved. We also study the quasi-pseudo-metrizability of\na topological ordered space $(X, \\tau, \\preccurlyeq)$. It is shown that if $(X,\n\\tau, \\preccurlyeq)$ is a ball transitive topological ordered $C$- and\n$I$-space such that $\\tau$ is metrizable, then its associated bitopological\nspace $(X,\\tau^{\\flat},\\tau^{\\natural})$ is quasi-pseudo-metrizable. This\nresult provides a partial affirmative answer to a problem in \\cite{KM}.\n",
"title": "Pairwise $k$-Semi-Stratifiable Bispaces and Topological Ordered Spaces"
} | null | null | [
"Mathematics"
]
| null | true | null | 19361 | null | Validated | null | null |
null | {
"abstract": " Internship assignment is a complicated process for universities since it is\nnecessary to take into account a multiplicity of variables to establish a\ncompromise between companies' requirements and student competencies acquired\nduring the university training. These variables build up a complex relations\nmap that requires the formulation of an exhaustive and rigorous conceptual\nscheme. In this research a domain ontological model is presented as support to\nthe student's decision making for opportunities of University studies level of\nthe University Lumiere Lyon 2 (ULL) education system. The ontology is designed\nand created using methodological approach offering the possibility of improving\nthe progressive creation, capture and knowledge articulation. In this paper, we\ndraw a balance taking the demands of the companies across the capabilities of\nthe students. This will be done through the establishment of an ontological\nmodel of an educational learners' profile and the internship postings which are\nwritten in a free text and using uncontrolled vocabulary. Furthermore, we\noutline the process of semantic matching which improves the quality of query\nresults.\n",
"title": "Ontology based system to guide internship assignment process"
} | null | null | null | null | true | null | 19362 | null | Default | null | null |
null | {
"abstract": " Quantum mechanical calculations had been previously applied to predict phase\nstability in many ternary and multinary nitride systems. While the predictions\nwere very accurate for the Ti-Al-N system, some discrepancies between theory\nand experiment were obtained in the case of other systems. Namely, in the case\nof Ta-Al-N, the calculations tend to overestimate the minimum Al content\nnecessary to obtain a metastable solid solution with a cubic structure. In this\nwork, we present a comprehensive study of the impact of vacancies on the phase\nfields in quasi-binary TaN-AlN and NbN-AlN systems. Our calculations clearly\nshow that presence of point defects strongly enlarges the cubic phase field in\nthe TaN-AlN system, while the effect is less pronounced in the NbN-AlN case.\nThe present phase stability predictions agree better with experimental\nobservations of physical vapour deposited thin films reported in the literature\nthan that based on perfect, non-defected structures. This study shows that a\nrepresentative structural model is crucial for a meaningful comparison with\nexperimental data.\n",
"title": "Vacancy-driven extended stability of cubic metastable Ta-Al-N and Nb-Al-N phases"
} | null | null | null | null | true | null | 19363 | null | Default | null | null |
null | {
"abstract": " This paper addresses the question: Why do neural dialog systems generate\nshort and meaningless replies? We conjecture that, in a dialog system, an\nutterance may have multiple equally plausible replies, causing the deficiency\nof neural networks in the dialog application. We propose a systematic way to\nmimic the dialog scenario in a machine translation system, and manage to\nreproduce the phenomenon of generating short and less meaningful sentences in\nthe translation setting, showing evidence of our conjecture.\n",
"title": "Why Do Neural Dialog Systems Generate Short and Meaningless Replies? A Comparison between Dialog and Translation"
} | null | null | null | null | true | null | 19364 | null | Default | null | null |
null | {
"abstract": " In this paper we tackle the problem of visually predicting surface friction\nfor environments with diverse surfaces, and integrating this knowledge into\nbiped robot locomotion planning. The problem is essential for autonomous robot\nlocomotion since diverse surfaces with varying friction abound in the real\nworld, from wood to ceramic tiles, grass or ice, which may cause difficulties\nor huge energy costs for robot locomotion if not considered. We propose to\nestimate friction and its uncertainty from visual estimation of material\nclasses using convolutional neural networks, together with probability\ndistribution functions of friction associated with each material. We then\nrobustly integrate the friction predictions into a hierarchical (footstep and\nfull-body) planning method using chance constraints, and optimize the same\ntrajectory costs at both levels of the planning method for consistency. Our\nsolution achieves fully autonomous perception and locomotion on slippery\nterrain, which considers not only friction and its uncertainty, but also\ncollision, stability and trajectory cost. We show promising friction prediction\nresults in real pictures of outdoor scenarios, and planning experiments on a\nreal robot facing surfaces with different friction.\n",
"title": "Material Recognition CNNs and Hierarchical Planning for Biped Robot Locomotion on Slippery Terrain"
} | null | null | null | null | true | null | 19365 | null | Default | null | null |
null | {
"abstract": " We present a new non-Archimedean model of evolutionary dynamics, in which the\ngenomes are represented by p-adic numbers. In this model the genomes have a\nvariable length, not necessarily bounded, in contrast with the classical models\nwhere the length is fixed. The time evolution of the concentration of a given\ngenome is controlled by a p-adic evolution equation. This equation depends on a\nfitness function f and on mutation measure Q. By choosing a mutation measure of\nGibbs type, and by using a p-adic version of the Maynard Smith Ansatz, we show\nthe existence of threshold function M_{c}(f,Q), such that the long term\nsurvival of a genome requires that its length grows faster than M_{c}(f,Q).\nThis implies that Eigen's paradox does not occur if the complexity of genomes\ngrows at the right pace. About twenty years ago, Scheuring and Poole, Jeffares,\nPenny proposed a hypothesis to explain Eigen's paradox. Our mathematical model\nshows that this biological hypothesis is feasible, but it requires p-adic\nanalysis instead of real analysis. More exactly, the Darwin-Eigen cycle\nproposed by Poole et al. takes place if the length of the genomes exceeds\nM_{c}(f,Q).\n",
"title": "Non-Archimedean Replicator Dynamics and Eigen's Paradox"
} | null | null | [
"Quantitative Biology"
]
| null | true | null | 19366 | null | Validated | null | null |
null | {
"abstract": " We present a new approach to the design of D-optimal experiments with\nmultivariate polynomial regressions on compact semi-algebraic design spaces. We\napply the moment-sum-of-squares hierarchy of semidefinite programming problems\nto solve numerically and approximately the optimal design problem. The geometry\nof the design is recovered with semidefinite programming duality theory and the\nChristoffel polynomial.\n",
"title": "D-optimal design for multivariate polynomial regression via the Christoffel function and semidefinite relaxations"
} | null | null | null | null | true | null | 19367 | null | Default | null | null |
null | {
"abstract": " We propose a statistical model for weighted temporal networks capable of\nmeasuring the level of heterogeneity in a financial system. Our model focuses\non the level of diversification of financial institutions; that is, whether\nthey are more inclined to distribute their assets equally among partners, or if\nthey rather concentrate their commitment towards a limited number of\ninstitutions. Crucially, a Markov property is introduced to capture time\ndependencies and to make our measures comparable across time. We apply the\nmodel on an original dataset of Austrian interbank exposures. The temporal span\nencompasses the onset and development of the financial crisis in 2008 as well\nas the beginnings of European sovereign debt crisis in 2011. Our analysis\nhighlights an overall increasing trend for network homogeneity, whereby core\nbanks have a tendency to distribute their market exposures more equally across\ntheir partners.\n",
"title": "A dynamic network model to measure exposure diversification in the Austrian interbank market"
} | null | null | null | null | true | null | 19368 | null | Default | null | null |
null | {
"abstract": " We report a Dynamical Cluster Approximation (DCA) investigation of the doped\nperiodic Anderson model (PAM) to explain the universal scaling in the Knight\nshift anomaly predicted by the phenomenological two-fluid model and confirmed\nin many heavy-fermion compounds. We calculate the quantitative evolution of the\norbital-dependent magnetic susceptibility and reproduce correctly the two-fluid\nprediction in a large range of doping and hybridization. Our results confirm\nthe presence of a temperature/energy scale $T^{\\ast}$ for the universal scaling\nand show distinctive behavors of the Knight shift anomaly in response to other\n\"orders\" at low temperatures. However, comparison with the temperature\nevolution of the calculated resistivity and quasiparticle spectral peak\nindicates a different characteristic temperature from $T^*$, in contradiction\nwith the experimental observation in CeCoIn$_5$ and other compounds. This\nreveals a missing piece in the current model calculations in explaining the\ntwo-fluid phenomenology.\n",
"title": "Universal scaling in the Knight shift anomaly of doped periodic Anderson model"
} | null | null | null | null | true | null | 19369 | null | Default | null | null |
null | {
"abstract": " This paper formalises the problem of online algorithm selection in the\ncontext of Reinforcement Learning. The setup is as follows: given an episodic\ntask and a finite number of off-policy RL algorithms, a meta-algorithm has to\ndecide which RL algorithm is in control during the next episode so as to\nmaximize the expected return. The article presents a novel meta-algorithm,\ncalled Epochal Stochastic Bandit Algorithm Selection (ESBAS). Its principle is\nto freeze the policy updates at each epoch, and to leave a rebooted stochastic\nbandit in charge of the algorithm selection. Under some assumptions, a thorough\ntheoretical analysis demonstrates its near-optimality considering the\nstructural sampling budget limitations. ESBAS is first empirically evaluated on\na dialogue task where it is shown to outperform each individual algorithm in\nmost configurations. ESBAS is then adapted to a true online setting where\nalgorithms update their policies after each transition, which we call SSBAS.\nSSBAS is evaluated on a fruit collection task where it is shown to adapt the\nstepsize parameter more efficiently than the classical hyperbolic decay, and on\nan Atari game, where it improves the performance by a wide margin.\n",
"title": "Reinforcement Learning Algorithm Selection"
} | null | null | null | null | true | null | 19370 | null | Default | null | null |
null | {
"abstract": " We construct periodic solutions of nonlinear wave equations using analytic\ncontinuation. The construction applies in particular to Einstein equations,\nleading to infinite-dimensional families of time-periodic solutions of the\nvacuum, or of the Einstein-Maxwell-dilaton-scalar\nfields-Yang-Mills-Higgs-Chern-Simons-$f(R)$ equations, with a negative\ncosmological constant.\n",
"title": "On periodic solutions of nonlinear wave equations, including Einstein equations with a negative cosmological constant"
} | null | null | null | null | true | null | 19371 | null | Default | null | null |
null | {
"abstract": " Attribute-based recognition models, due to their impressive performance and\ntheir ability to generalize well on novel categories, have been widely adopted\nfor many computer vision applications. However, usually both the attribute\nvocabulary and the class-attribute associations have to be provided manually by\ndomain experts or large number of annotators. This is very costly and not\nnecessarily optimal regarding recognition performance, and most importantly, it\nlimits the applicability of attribute-based models to large scale data sets. To\ntackle this problem, we propose an end-to-end unsupervised attribute learning\napproach. We utilize online text corpora to automatically discover a salient\nand discriminative vocabulary that correlates well with the human concept of\nsemantic attributes. Moreover, we propose a deep convolutional model to\noptimize class-attribute associations with a linguistic prior that accounts for\nnoise and missing data in text. In a thorough evaluation on ImageNet, we\ndemonstrate that our model is able to efficiently discover and learn semantic\nattributes at a large scale. Furthermore, we demonstrate that our model\noutperforms the state-of-the-art in zero-shot learning on three data sets:\nImageNet, Animals with Attributes and aPascal/aYahoo. Finally, we enable\nattribute-based learning on ImageNet and will share the attributes and\nassociations for future research.\n",
"title": "Automatic Discovery, Association Estimation and Learning of Semantic Attributes for a Thousand Categories"
} | null | null | [
"Computer Science"
]
| null | true | null | 19372 | null | Validated | null | null |
null | {
"abstract": " In this paper, a scale mixture of Normal distributions model is developed for\nclassification and clustering of data having outliers and missing values. The\nclassification method, based on a mixture model, focuses on the introduction of\nlatent variables that gives us the possibility to handle sensitivity of model\nto outliers and to allow a less restrictive modelling of missing data.\nInference is processed through a Variational Bayesian Approximation and a\nBayesian treatment is adopted for model learning, supervised classification and\nclustering.\n",
"title": "Variational Bayesian Inference For A Scale Mixture Of Normal Distributions Handling Missing Data"
} | null | null | null | null | true | null | 19373 | null | Default | null | null |
null | {
"abstract": " We study the systematic numerical approximation of a class of Allen-Cahn type\nproblems modeling the motion of phase interfaces. The common feature of these\nmodels is an underlying gradient flow structure which gives rise to a decay of\nan associated energy functional along solution trajectories. We first study the\ndiscretization in space by a conforming Galerkin approximation of a variational\nprinciple which characterizes smooth solutions of the problem. Well-posedness\nof the resulting semi-discretization is established and the energy decay along\ndiscrete solution trajectories is proven. A problem adapted implicit\ntime-stepping scheme is then proposed and we establish its well-posed and decay\nof the free energy for the fully discrete scheme. Some details about the\nnumerical realization by finite elements are discussed, in particular the\niterative solution of the nonlinear problems arising in every time-step. The\ntheoretical results are illustrated by numerical tests which also provide\nfurther evidence for asymptotic expansions of the interface velocities derived\nby Alber et al.\n",
"title": "Energy stable discretization of Allen-Cahn type problems modeling the motion of phase boundaries"
} | null | null | null | null | true | null | 19374 | null | Default | null | null |
null | {
"abstract": " As a fundamental challenge in vast disciplines, link prediction aims to\nidentify potential links in a network based on the incomplete observed\ninformation, which has broad applications ranging from uncovering missing\nprotein-protein interaction to predicting the evolution of networks. One of the\nmost influential methods rely on similarity indices characterized by the common\nneighbors or its variations. We construct a hidden space mapping a network into\nEuclidean space based solely on the connection structures of a network.\nCompared with real geographical locations of nodes, our reconstructed locations\nare in conformity with those real ones. The distances between nodes in our\nhidden space could serve as a novel similarity metric in link prediction. In\naddition, we hybrid our hidden space method with other state-of-the-art\nsimilarity methods which substantially outperforms the existing methods on the\nprediction accuracy. Hence, our hidden space reconstruction model provides a\nfresh perspective to understand the network structure, which in particular\ncasts a new light on link prediction.\n",
"title": "Hidden space reconstruction inspires link prediction in complex networks"
} | null | null | null | null | true | null | 19375 | null | Default | null | null |
null | {
"abstract": " In this paper, we consider nonlinear equations involving the fractional\np-Laplacian $$ (-\\lap)_p^s u(x)) \\equiv C_{n,s,p} PV \\int_{\\mathbb{R}^n}\n\\frac{|u(x)-u(y)|^{p-2}[u(x)-u(y)]}{|x-z|^{n+ps}} dz= f(x,u).$$\nWe prove a {\\em maximum principle for anti-symmetric functions} and obtain\nother key ingredients for carrying on the method of moving planes, such as {\\em\na key boundary estimate lemma}. Then we establish radial symmetry and\nmonotonicity for positive solutions to semilinear equations involving the\nfractional p-Laplacian in a unit ball and in the whole space. We believe that\nthe methods developed here can be applied to a variety of problems involving\nnonlinear nonlocal operators.\n",
"title": "Maximum principles for the fractional p-Laplacian and symmetry of solutions"
} | null | null | [
"Mathematics"
]
| null | true | null | 19376 | null | Validated | null | null |
null | {
"abstract": " In recent works we have constructed axisymmetric solutions to the\nEuler-Poisson equations which give mathematical models of slowly uniformly\nrotating gaseous stars. We try to extend this result to the study of solutions\nof the Einstein-Euler equations in the framework of the general theory of\nrelativity. Although many interesting studies have been done about axisymmetric\nmetric in the general theory of relativity, they are restricted to the region\nof the vacuum. Mathematically rigorous existence theorem of the axisymmetric\ninterior solutions of the stationary metric corresponding to the\nenergy-momentum tensor of the perfect fluid with non-zero pressure may be not\nyet established until now except only one found in the pioneering work by U.\nHeilig done in 1993. In this article, along a different approach to that of\nHeilig's work, axisymmetric stationary solutions of the Einstein-Euler\nequations are constructed near those of the Euler-Poisson equations when the\nspeed of light is sufficiently large in the considered system of units, or,\nwhen the gravitational field is sufficiently weak.\n",
"title": "On slowly rotating axisymmetric solutions of the Einstein-Euler equations"
} | null | null | [
"Mathematics"
]
| null | true | null | 19377 | null | Validated | null | null |
null | {
"abstract": " We implement the coupled cluster method to very high orders of approximation\nto study the spin-$\\frac{1}{2}$ $J_{1}$--$J_{2}$ Heisenberg model on a\ncross-striped square lattice. Every nearest-neighbour pair of sites on the\nsquare lattice has an isotropic antiferromagnetic exchange bond of strength\n$J_{1}>0$, while the basic square plaquettes in alternate columns have either\nboth or neither next-nearest-neighbour (diagonal) pairs of sites connected by\nan equivalent frustrating bond of strength $J_{2} \\equiv \\alpha J_{1} > 0$. By\nstudying the magnetic order parameter (i.e., the average local on-site\nmagnetization) in the range $0 \\leq \\alpha \\leq 1$ of the frustration parameter\nwe find that the quasiclassical antiferromagnetic Néel and (so-called)\ndouble Néel states form the stable ground-state phases in the respective\nregions $\\alpha < \\alpha_{1a}^{c} = 0.46(1)$ and $\\alpha > \\alpha_{1b}^{c} =\n0.615(5)$. The double Néel state has Néel\n($\\cdots\\uparrow\\downarrow\\uparrow\\downarrow\\cdots$) ordering along the\n(column) direction parallel to the stripes of squares with both or no $J_{2}$\nbonds, and spins alternating in a pairwise\n($\\cdots\\uparrow\\uparrow\\downarrow\\downarrow\\uparrow\\uparrow\\downarrow\\downarrow\\cdots$)\nfashion along the perpendicular (row) direction, so that the parallel pairs\noccur on squares with both $J_{2}$ bonds present. Further explicit calculations\nof both the triplet spin gap and the zero-field uniform transverse magnetic\nsusceptibility provide compelling evidence that the ground-state phase over all\nor most of the intermediate regime $\\alpha_{1a}^{c} < \\alpha < \\alpha_{1b}^{c}$\nis a gapped state with no discernible long-range magnetic order.\n",
"title": "Gapped paramagnetic state in a frustrated spin-$\\frac{1}{2}$ Heisenberg antiferromagnet on the cross-striped square lattice"
} | null | null | [
"Physics"
]
| null | true | null | 19378 | null | Validated | null | null |
null | {
"abstract": " Clouds have a strong impact on the climate of planetary atmospheres. The\npotential scattering greenhouse effect of CO2 ice clouds in the atmospheres of\nterrestrial extrasolar planets is of particular interest because it might\ninfluence the position and thus the extension of the outer boundary of the\nclassic habitable zone around main sequence stars. Here, the impact of CO2 ice\nclouds on the surface temperatures of terrestrial planets with CO2 dominated\natmospheres, orbiting different types of stars is studied. Additionally, their\ncorresponding effect on the position of the outer habitable zone boundary is\nevaluated. For this study, a radiative-convective atmospheric model is used the\ncalculate the surface temperatures influenced by CO2 ice particles. The clouds\nare included using a parametrised cloud model. The atmospheric model includes a\ngeneral discrete ordinate radiative transfer that can describe the anisotropic\nscattering by the cloud particles accurately. A net scattering greenhouse\neffect caused by CO2 clouds is only obtained in a rather limited parameter\nrange which also strongly depends on the stellar effective temperature. For\ncool M-stars, CO2 clouds only provide about 6 K of additional greenhouse\nheating in the best case scenario. On the other hand, the surface temperature\nfor a planet around an F-type star can be increased by 30 K if carbon dioxide\nclouds are present. Accordingly, the extension of the habitable zone due to\nclouds is quite small for late-type stars. Higher stellar effective\ntemperatures, on the other hand, can lead to outer HZ boundaries about 0.5 au\nfarther out than the corresponding clear-sky values.\n",
"title": "Clouds in the atmospheres of extrasolar planets. V. The impact of CO2 ice clouds on the outer boundary of the habitable zone"
} | null | null | null | null | true | null | 19379 | null | Default | null | null |
null | {
"abstract": " Magnetic resonance imaging (MRI) has been proposed as a complimentary method\nto measure bone quality and assess fracture risk. However, manual segmentation\nof MR images of bone is time-consuming, limiting the use of MRI measurements in\nthe clinical practice. The purpose of this paper is to present an automatic\nproximal femur segmentation method that is based on deep convolutional neural\nnetworks (CNNs). This study had institutional review board approval and written\ninformed consent was obtained from all subjects. A dataset of volumetric\nstructural MR images of the proximal femur from 86 subject were\nmanually-segmented by an expert. We performed experiments by training two\ndifferent CNN architectures with multiple number of initial feature maps and\nlayers, and tested their segmentation performance against the gold standard of\nmanual segmentations using four-fold cross-validation. Automatic segmentation\nof the proximal femur achieved a high dice similarity score of 0.94$\\pm$0.05\nwith precision = 0.95$\\pm$0.02, and recall = 0.94$\\pm$0.08 using a CNN\narchitecture based on 3D convolution exceeding the performance of 2D CNNs. The\nhigh segmentation accuracy provided by CNNs has the potential to help bring the\nuse of structural MRI measurements of bone quality into clinical practice for\nmanagement of osteoporosis.\n",
"title": "Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks"
} | null | null | null | null | true | null | 19380 | null | Default | null | null |
null | {
"abstract": " In Crowdfunding platforms, people turn their prototype ideas into real\nproducts by raising money from the crowd, or invest in someone else's projects.\nIn reward-based crowdfunding platforms such as Kickstarter and Indiegogo,\nselecting accurate reward delivery duration becomes crucial for creators,\nbackers, and platform providers to keep the trust between the creators and the\nbackers, and the trust between the platform providers and users. According to\nKickstarter, 35% backers did not receive rewards on time. Unfortunately, little\nis known about on-time and late reward delivery projects, and there is no prior\nwork to estimate reward delivery duration. To fill the gap, in this paper, we\n(i) extract novel features that reveal latent difficulty levels of project\nrewards; (ii) build predictive models to identify whether a creator will\ndeliver all rewards in a project on time or not; and (iii) build a regression\nmodel to estimate accurate reward delivery duration (i.e., how long it will\ntake to produce and deliver all the rewards). Experimental results show that\nour models achieve good performance -- 82.5% accuracy, 78.1 RMSE, and 0.108\nNRMSE at the first 5% of the longest reward delivery duration.\n",
"title": "Identifying On-time Reward Delivery Projects with Estimating Delivery Duration on Kickstarter"
} | null | null | null | null | true | null | 19381 | null | Default | null | null |
null | {
"abstract": " Learning to infer Bayesian posterior from a few-shot dataset is an important\nstep towards robust meta-learning due to the model uncertainty inherent in the\nproblem. In this paper, we propose a novel Bayesian model-agnostic\nmeta-learning method. The proposed method combines scalable gradient-based\nmeta-learning with nonparametric variational inference in a principled\nprobabilistic framework. During fast adaptation, the method is capable of\nlearning complex uncertainty structure beyond a point estimate or a simple\nGaussian approximation. In addition, a robust Bayesian meta-update mechanism\nwith a new meta-loss prevents overfitting during meta-update. Remaining an\nefficient gradient-based meta-learner, the method is also model-agnostic and\nsimple to implement. Experiment results show the accuracy and robustness of the\nproposed method in various tasks: sinusoidal regression, image classification,\nactive learning, and reinforcement learning.\n",
"title": "Bayesian Model-Agnostic Meta-Learning"
} | null | null | null | null | true | null | 19382 | null | Default | null | null |
null | {
"abstract": " We discuss the distributed matching scheme in accelerators where control of\ntransverse beam phase space, oscillation, and transport is accomplished by\nflexible distribution of focusing elements beyond dedicated matching sections.\nBesides freeing accelerator design from fixed matching sections, such a scheme\nhas many operational advantages, and enables fluid optics manipulation not\npossible in conventional schemes. Combined with an interpolation scheme this\ncan bring about a new paradigm for efficient, flexible, and robust optics\ncontrol. A rigorous and deterministic algorithm is developed for its\nrealization. The algorithm is a matching tool in its own right with unique\ncharacteristics in robustness and determinism. The beam phase space dynamics is\nnaturally integrated into the algorithm, instead of being treated as generic\nnumerical parameters as in traditional schemes. It is applicable to a wider\nrange of problems, such as trading-off between competing options for desired\nmachine states.\n",
"title": "Distributed matching scheme and a flexible deterministic matching algorithm for arbitrary systems"
} | null | null | null | null | true | null | 19383 | null | Default | null | null |
null | {
"abstract": " We complement the characterization of the graph products of cyclic groups\n$G(\\Gamma, \\mathfrak{p})$ admitting a Polish group topology of [9] with the\nfollowing result. Let $G = G(\\Gamma, \\mathfrak{p})$, then the following are\nequivalent: (i) there is a metric on $\\Gamma$ which induces a separable\ntopology in which $E_{\\Gamma}$ is closed; (ii) $G(\\Gamma, \\mathfrak{p})$ is\nembeddable into a Polish group; (iii) $G(\\Gamma, \\mathfrak{p})$ is embeddable\ninto a non-Archimedean Polish group. We also construct left-invariant separable\ngroup ultrametrics for $G = G(\\Gamma, \\mathfrak{p})$ and $\\Gamma$ a closed\ngraph on the Baire space, which is of independent interest.\n",
"title": "Group Metrics for Graph Products of Cyclic Groups"
} | null | null | null | null | true | null | 19384 | null | Default | null | null |
null | {
"abstract": " Multi-Task Learning (MTL) can enhance a classifier's generalization\nperformance by learning multiple related tasks simultaneously. Conventional MTL\nworks under the offline or batch setting, and suffers from expensive training\ncost and poor scalability. To address such inefficiency issues, online learning\ntechniques have been applied to solve MTL problems. However, most existing\nalgorithms of online MTL constrain task relatedness into a presumed structure\nvia a single weight matrix, which is a strict restriction that does not always\nhold in practice. In this paper, we propose a robust online MTL framework that\novercomes this restriction by decomposing the weight matrix into two\ncomponents: the first one captures the low-rank common structure among tasks\nvia a nuclear norm and the second one identifies the personalized patterns of\noutlier tasks via a group lasso. Theoretical analysis shows the proposed\nalgorithm can achieve a sub-linear regret with respect to the best linear model\nin hindsight. Even though the above framework achieves good performance, the\nnuclear norm that simply adds all nonzero singular values together may not be a\ngood low-rank approximation. To improve the results, we use a log-determinant\nfunction as a non-convex rank approximation. The gradient scheme is applied to\noptimize log-determinant function and can obtain a closed-form solution for\nthis refined problem. Experimental results on a number of real-world\napplications verify the efficacy of our method.\n",
"title": "Robust Online Multi-Task Learning with Correlative and Personalized Structures"
} | null | null | null | null | true | null | 19385 | null | Default | null | null |
null | {
"abstract": " In this note, we discuss the cobordism maps on periodic Floer homology(PFH)\ninduced by Lefschetz fibration. In the first part of the note, we define the\ncobordism maps on PFH induced by Lefschetz fibration via Seiberg Witten theory\nand the isomorphism between PFH and Seiberg Witten cohomology. The second part\nis to define the cobordism maps induced by Lefschetz fibration provided that\nthe cobordism satisfies certain conditions. Under certain monotone assumptions,\nwe show that these two definitions in fact are equivalent.\n",
"title": "Cobordism maps on PFH induced by Lefschetz fibration over higher genus base"
} | null | null | null | null | true | null | 19386 | null | Default | null | null |
null | {
"abstract": " We give necessary and sufficient conditions for the Zhang-Liu matrices to be\ndiagonalizable over arbitrary fields and provide the eigen-decomposition when\nit is possible. We use this result to calculate the order of these matrices\nover any arbitrary field. This generalizes a result of the second author.\n",
"title": "A short note on the order of the Zhang-Liu matrices over arbitrary fields"
} | null | null | null | null | true | null | 19387 | null | Default | null | null |
null | {
"abstract": " This is the Proceedings of the 2017 ICML Workshop on Human Interpretability\nin Machine Learning (WHI 2017), which was held in Sydney, Australia, August 10,\n2017. Invited speakers were Tony Jebara, Pang Wei Koh, and David Sontag.\n",
"title": "Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017)"
} | null | null | null | null | true | null | 19388 | null | Default | null | null |
null | {
"abstract": " We study the quantum phase transition between a paramagnetic and\nferromagnetic metal in the presence of Rashba spin-orbit coupling in one\ndimension. Using bosonization, we analyze the transition by means of\nrenormalization group, controlled by an $\\varepsilon$-expansion around the\nupper critical dimension of two. We show that the presence of Rashba spin-orbit\ncoupling allows for a new nonlinear term in the bosonized action, which\ngenerically leads to a fluctuation driven first-order transition. We further\ndemonstrate that the Euclidean action of this system maps onto a classical\nsmectic-A -- C phase transition in a magnetic field in two dimensions. We show\nthat the smectic transition is second-order and is controlled by a new critical\npoint.\n",
"title": "Ferromagnetic transition in a one-dimensional spin-orbit-coupled metal and its mapping to a critical point in smectic liquid crystals"
} | null | null | [
"Physics"
]
| null | true | null | 19389 | null | Validated | null | null |
null | {
"abstract": " A 4-dimensional Riemannian manifold equipped with a circulant structure,\nwhich is an isometry with respect to the metric and its fourth power is the\nidentity, is considered. The almost product manifold associated with the\nconsidered manifold is studied. The relation between the covariant derivatives\nof the almost product structure and the circulant structure is obtained. The\nconditions for the covariant derivative of the circulant structure, which imply\nthat an almost product manifold belongs to each of the basic classes of the\nStaikova-Gribachev classification, are given.\n",
"title": "Riemannian almost product manifolds generated by a circulant structure"
} | null | null | [
"Mathematics"
]
| null | true | null | 19390 | null | Validated | null | null |
null | {
"abstract": " Modern software systems provide many configuration options which\nsignificantly influence their non-functional properties. To understand and\npredict the effect of configuration options, several sampling and learning\nstrategies have been proposed, albeit often with significant cost to cover the\nhighly dimensional configuration space. Recently, transfer learning has been\napplied to reduce the effort of constructing performance models by transferring\nknowledge about performance behavior across environments. While this line of\nresearch is promising to learn more accurate models at a lower cost, it is\nunclear why and when transfer learning works for performance modeling. To shed\nlight on when it is beneficial to apply transfer learning, we conducted an\nempirical study on four popular software systems, varying software\nconfigurations and environmental conditions, such as hardware, workload, and\nsoftware versions, to identify the key knowledge pieces that can be exploited\nfor transfer learning. Our results show that in small environmental changes\n(e.g., homogeneous workload change), by applying a linear transformation to the\nperformance model, we can understand the performance behavior of the target\nenvironment, while for severe environmental changes (e.g., drastic workload\nchange) we can transfer only knowledge that makes sampling more efficient,\ne.g., by reducing the dimensionality of the configuration space.\n",
"title": "Transfer Learning for Performance Modeling of Configurable Systems: An Exploratory Analysis"
} | null | null | null | null | true | null | 19391 | null | Default | null | null |
null | {
"abstract": " We review André Luiz Barbosa's paper \"P != NP Proof,\" in which the classes\nP and NP are generalized and claimed to be proven separate. We highlight\ninherent ambiguities in Barbosa's definitions, and show that attempts to\nresolve this ambiguity lead to flaws in the proof of his main result.\n",
"title": "Critique of Barbosa's \"P != NP Proof\""
} | null | null | null | null | true | null | 19392 | null | Default | null | null |
null | {
"abstract": " We consider the minimax setup for the two-armed bandit problem as applied to\ndata processing if there are two alternative processing methods available with\ndifferent a priori unknown efficiencies. One should determine the most\neffective method and provide its predominant application. To this end we use\nthe mirror descent algorithm (MDA). It is well-known that corresponding minimax\nrisk has the order $N^{1/2}$ with $N$ being the number of processed data. We\nimprove significantly the theoretical estimate of the factor using Monte-Carlo\nsimulations. Then we propose a parallel version of the MDA which allows\nprocessing of data by packets in a number of stages. The usage of parallel\nversion of the MDA ensures that total time of data processing depends mostly on\nthe number of packets but not on the total number of data. It is quite\nunexpectedly that the parallel version behaves unlike the ordinary one even if\nthe number of packets is large. Moreover, the parallel version considerably\nimproves control performance because it provides significantly smaller value of\nthe minimax risk. We explain this result by considering another parallel\nmodification of the MDA which behavior is close to behavior of the ordinary\nversion. Our estimates are based on invariant descriptions of the algorithms.\nAll estimates are obtained by Monte-Carlo simulations. It's worth noting that\nparallel version performs well only for methods with close efficiencies. If\nefficiencies differ significantly then one should use the combined algorithm\nwhich at initial sufficiently short control horizon uses ordinary version and\nthen switches to the parallel version of the MDA.\n",
"title": "Two-Armed Bandit Problem, Data Processing, and Parallel Version of the Mirror Descent Algorithm"
} | null | null | null | null | true | null | 19393 | null | Default | null | null |
null | {
"abstract": " Traditional intelligent fault diagnosis of rolling bearings work well only\nunder a common assumption that the labeled training data (source domain) and\nunlabeled testing data (target domain) are drawn from the same distribution.\nWhen the distribution changes, most fault diagnosis models need to be rebuilt\nfrom scratch using newly recollected labeled training data. However, it is\nexpensive or impossible to annotate huge amount of training data to rebuild\nsuch new model. Meanwhile, large amounts of labeled training data have not been\nfully utilized yet, which is apparently a waste of resources. As one of the\nimportant research directions of transfer learning, domain adaptation (DA)\ntypically aims at minimizing the differences between distributions of different\ndomains in order to minimize the cross-domain prediction error by taking full\nadvantage of information coming from both source and target domains. In this\npaper, we present one of the first studies on unsupervised DA in the field of\nfault diagnosis of rolling bearings under varying working conditions and a\nnovel diagnosis strategy based on unsupervised DA using subspace alignment (SA)\nis proposed. After processed by unsupervised DA with SA, the distributions of\ntraining data and testing data become close and the classifier trained on\ntraining data can be used to classify the testing data. Experimental results on\nthe 60 domain adaptation diagnosis problems under varying working condition in\nCase Western Reserve benchmark data and 12 domain adaptation diagnosis problems\nunder varying working conditions in our new data are given to demonstrate the\neffectiveness of the proposed method. The proposed methods can effectively\ndistinguish not only bearing faults categories but also fault severities.\n",
"title": "Bearing fault diagnosis under varying working condition based on domain adaptation"
} | null | null | null | null | true | null | 19394 | null | Default | null | null |
null | {
"abstract": " In one perspective, the main theme of this research revolves around the\ninverse problem in the context of general rough sets that concerns the\nexistence of rough basis for given approximations in a context. Granular\noperator spaces and variants were recently introduced by the present author as\nan optimal framework for anti-chain based algebraic semantics of general rough\nsets and the inverse problem. In the framework, various sub-types of crisp and\nnon-crisp objects are identifiable that may be missed in more restrictive\nformalism. This is also because in the latter cases concepts of complementation\nand negation are taken for granted - while in reality they have a complicated\ndialectical basis. This motivates a general approach to dialectical rough sets\nbuilding on previous work of the present author and figures of opposition. In\nthis paper dialectical rough logics are invented from a semantic perspective, a\nconcept of dialectical predicates is formalised, connection with dialetheias\nand glutty negation are established, parthood analyzed and studied from the\nviewpoint of classical and dialectical figures of opposition by the present\nauthor. Her methods become more geometrical and encompass parthood as a primary\nrelation (as opposed to roughly equivalent objects) for algebraic semantics.\n",
"title": "Dialectical Rough Sets, Parthood and Figures of Opposition-1"
} | null | null | [
"Computer Science",
"Mathematics"
]
| null | true | null | 19395 | null | Validated | null | null |
null | {
"abstract": " In this paper we introduce an easily verifiable sufficient condition to\ndetermine whether an algebra is quasi-hereditary. In the case of monomial\nalgebras, we give conditions that are both necessary and sufficient to show\nwhether an algebra is quasi-hereditary.\n",
"title": "On quasi-hereditary algebras"
} | null | null | null | null | true | null | 19396 | null | Default | null | null |
null | {
"abstract": " We study the problems of clustering locally asymptotically self-similar\nstochastic processes, when the true number of clusters is priorly known. A new\ncovariance-based dissimilarity measure is introduced, from which the so-called\napproximately asymptotically consistent clustering algorithms are obtained. In\na simulation study, clustering data sampled from multifractional Brownian\nmotions is performed to illustrate the approximated asymptotic consistency of\nthe proposed algorithms.\n",
"title": "Clustering Analysis on Locally Asymptotically Self-similar Processes with Known Number of Clusters"
} | null | null | null | null | true | null | 19397 | null | Default | null | null |
null | {
"abstract": " The OSIRIS-REx Visible and Infrared Spectrometer (OVIRS) is a point\nspectrometer covering the spectral range of 0.4 to 4.3 microns (25,000-2300\ncm-1). Its primary purpose is to map the surface composition of the asteroid\nBennu, the target asteroid of the OSIRIS-REx asteroid sample return mission.\nThe information it returns will help guide the selection of the sample site. It\nwill also provide global context for the sample and high spatial resolution\nspectra that can be related to spatially unresolved terrestrial observations of\nasteroids. It is a compact, low-mass (17.8 kg), power efficient (8.8 W\naverage), and robust instrument with the sensitivity needed to detect a 5%\nspectral absorption feature on a very dark surface (3% reflectance) in the\ninner solar system (0.89-1.35 AU). It, in combination with the other\ninstruments on the OSIRIS-REx Mission, will provide an unprecedented view of an\nasteroid's surface.\n",
"title": "The OSIRIS-REx Visible and InfraRed Spectrometer (OVIRS): Spectral Maps of the Asteroid Bennu"
} | null | null | null | null | true | null | 19398 | null | Default | null | null |
null | {
"abstract": " We prove boundedness results for integral operators of fractional type and\ntheir higher order commutators between weighted spaces, including $L^p$-$L^q$,\n$L^p$-$BMO$ and $L^p$-Lipschitz estimates. The kernels of such operators\nsatisfy certain size condition and a Lipschitz type regularity, and the symbol\nof the commutator belongs to a Lipschitz class. We also deal with commutators\nof fractional type operators with less regular kernels satisfying a\nHörmander's type inequality. As far as we know, these last results are new\neven in the unweighted case. Moreover, we give a characterization result\ninvolving symbols of the commutators and continuity results for extreme values\nof $p$.\n",
"title": "The effect of the smoothness of fractional type operators over their commutators with Lipschitz symbols on weighted spaces"
} | null | null | null | null | true | null | 19399 | null | Default | null | null |
null | {
"abstract": " We consider a large portfolio limit where the asset prices evolve according\ncertain stochastic volatility models with default upon hitting a lower barrier.\nWhen the asset prices and the volatilities are correlated via systemic Brownian\nMotions, that limit exist and it is described by a SPDE on the positive\nhalf-space with Dirichlet boundary conditions which has been studied in\n\\cite{HK17}. We study the convergence of the total mass of a solution to this\nstochastic initial-boundary value problem when the mean-reversion coefficients\nof the volatilities are multiples of a parameter that tends to infinity. When\nthe volatilities of the volatilities are multiples of the square root of the\nsame parameter, the convergence is extremely weak. On the other hand, when the\nvolatilities of the volatilities are independent of this exploding parameter,\nthe volatilities converge to their means and we can have much better\napproximations. Our aim is to use such approximations to improve the accuracy\nof certain risk-management methods in markets where fast volatility\nmean-reversion is observed.\n",
"title": "Fast mean-reversion asymptotics for large portfolios of stochastic volatility models"
} | null | null | null | null | true | null | 19400 | null | Default | null | null |
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