Under the auspices of the Computational Complexity Foundation (CCF) REPORTS > AUTHORS > PHILIPPE MOSER:
All reports by Author Philippe Moser:

TR07-051 | 18th April 2007
Pilar Albert, Elvira Mayordomo, Philippe Moser

#### Bounded Pushdown dimension vs Lempel Ziv information density

In this paper we introduce a variant of pushdown dimension called bounded pushdown (BPD) dimension, that measures the density of information contained in a sequence, relative to a BPD automata, i.e. a finite state machine equipped with an extra infinite memory stack, with the additional requirement that every input symbol ... more >>>

TR05-089 | 30th July 2005
Xiaoyang Gu, Jack H. Lutz, Philippe Moser

#### Dimensions of Copeland-Erdos Sequences

The base-$k$ {\em Copeland-Erd\"os sequence} given by an infinite
set $A$ of positive integers is the infinite
sequence $\CE_k(A)$ formed by concatenating the base-$k$
representations of the elements of $A$ in numerical
order. This paper concerns the following four
quantities.
\begin{enumerate}[$\bullet$]
\item
The {\em finite-state dimension} $\dimfs (\CE_k(A))$,
a finite-state ... more >>>

TR05-060 | 30th May 2005
Philippe Moser

#### Generic Density and Small Span Theorem

We refine the genericity concept of Ambos-Spies et al, by assigning a real number in $[0,1]$ to every generic set, called its generic density.
We construct sets of generic density any E-computable real in $[0,1]$.
We also introduce strong generic density, and show that it is related to packing ... more >>>

TR05-045 | 12th April 2005
Philippe Moser

#### Martingale Families and Dimension in P

Revisions: 1

We introduce a new measure notion on small complexity classes (called F-measure), based on martingale families,
that get rid of some drawbacks of previous measure notions:
martingale families can make money on all strings,
and yield random sequences with an equal frequency of 0's and 1's.
As applications to F-measure,
more >>>

TR03-046 | 11th June 2003
Philippe Moser

#### Locally Computed Baire's Categories on Small Complexity Classes

We strengthen an earlier notion of
resource-bounded Baire's categories, and define
resource bounded Baire's categories on small complexity classes such as P, QP, SUBEXP
and on probabilistic complexity classes such as BPP.
We give an alternative characterization of meager sets via resource-bounded
Banach Mazur games.
We show that the class ... more >>>

TR03-040 | 3rd June 2003
Philippe Moser

#### RP is Small in SUBEXP else ZPP equals PSPACE and NP equals EXP

We use recent results on the hardness of resource-bounded
Kolmogorov random strings, to prove that RP is small in SUBEXP
else ZPP=PSPACE and NP=EXP.
We also prove that if NP is not small in SUBEXP, then
NP=AM, improving a former result which held for the measure ... more >>>

TR03-029 | 1st April 2003
Philippe Moser

#### BPP has effective dimension at most 1/2 unless BPP=EXP

We prove that BPP has Lutz's p-dimension at most 1/2 unless BPP equals EXP.
Next we show that BPP has Lutz's p-dimension zero unless BPP equals EXP
on infinitely many input lengths.
We also prove that BPP has measure zero in the smaller complexity
class ... more >>>

TR02-058 | 25th September 2002
Philippe Moser

#### A generalization of Lutz's measure to probabilistic classes

We extend Lutz's measure to probabilistic classes, and obtain notions of measure on probabilistic complexity classes
C
such as BPP , BPE and BPEXP. Unlike former attempts,
all our measure notions satisfy all three Lutz's measure axioms, that is
every singleton {L} has measure zero ... more >>>

TR02-015 | 13th February 2002
Philippe Moser

#### ZPP is hard unless RP is small

Revisions: 1

We use Lutz's resource bounded measure theory to prove that either \tbf{RP} is
small or \tbf{ZPP} is hard. More precisely we prove that if \tbf{RP} has not p-measure zero, then \tbf{EXP} is contained
in $\mbf{ZPP}/n$.
We also show that if \tbf{RP} has not p-measure zero,
\tbf{EXP} equals ... more >>>

TR02-006 | 8th November 2001
Philippe Moser

#### Random nondeterministic real functions and Arthur Merlin games

Revisions: 1

We construct a nondeterministic analogue to \textbf{APP}, denoted
\textbf{NAPP}; which is the set of all real valued functions
$f: \{ 0,1 \}^{*} \rightarrow [0,1]$, that are approximable within 1/$k$,
by a probabilistic nondeterministic transducer, in time poly($n,1^{k}$).
We show that the subset of all Boolean ... more >>>

TR01-068 | 19th September 2001
Philippe Moser

#### Relative to P, APP and promise-BPP are the same

Revisions: 1

$\mathbf{APP}$, the class of real functions
promise-$\mathbf{BPP}$. First
we construct a mapping that maps every function in $\mathbf{APP}$ to a promise problem
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