In this paper we show that, in case of uncertainties during the estimation, overconfident posterior probabilities tend to mislead the performance of soft-decoders. Maximum likeliho...
The basic idea of an algebraic approach to learning Bayesian network (BN) structures is to represent every BN structure by a certain uniquely determined vector, called the standar...
Multiplysectioned Bayesian networks provide a probabilistic framework for reasoning about uncertain domains in cooperative multiagent systems. Several advances have been made in r...
We study computational problems that arise in the context of iterated dominance in anonymous games, and show that deciding whether a game can be solved by means of iterated weak d...
The problem of approximate parameterized string searching consists of finding, for a given text t = t1t2 ...tn and pattern p = p1p2 ...pm over respective alphabets Σt and Σp, t...