Many perception, reasoning, and learning problems can be expressed as Bayesian inference. We point out that formulating a problem as Bayesian inference implies specifying a probabi...
Many NLP tasks need accurate knowledge for semantic inference. To this end, mostly WordNet is utilized. Yet WordNet is limited, especially for inference between predicates. To hel...
Identification in the limit, originally due to Gold [10], is a widely used computation model for inductive inference and human language acquisition. We consider a nonconstructive ...
C programs can be difficult to debug due to lax type enforcement and low-level access to memory. We present a dynamic analysis for C that checks heap snapshots for consistency wit...
Background: Popular methods to reconstruct molecular phylogenies are based on multiple sequence alignments, in which addition or removal of data may change the resulting tree topo...
Olivier Bastien, Philippe Ortet, Sylvaine Roy, Eri...