A Concise Function Representation for Faster Exact MPE and Constrained
  Optimisation in Graphical Models
  We propose a novel concise function representation for graphical models, a
central theoretical framework that provides the basis for many reasoning tasks.
We then show how we exploit our concise representation based on deterministic
finite state automata within Bucket Elimination (BE), a general approach based
on the concept of variable elimination that accommodates many inference and
optimisation tasks such as most probable explanation and constrained
optimisation. We denote our version of BE as FABE. By using our concise
representation within FABE, we dramatically improve the performance of BE in
terms of runtime and memory requirements. Results on standard benchmarks
obtained using an established experimental methodology show that FABE often
outperforms the best available approach (RBFAOO), leading to significant
runtime improvements (up to 2 orders of magnitude in our tests).
