We present a new algorithm for conformant probabilistic planning, which for a given horizon produces a plan that maximizes the probability of success under quantified uncertainty ...
Abstract. In computer networks (and, say, transportation networks), we can consider the situation where each user has its own routing decision so as to minimize noncooperatively th...
In many domains, we are interested in analyzing the structure of the underlying distribution, e.g., whether one variable is a direct parent of the other. Bayesian model selection a...
Wepresent the prototype of a software system, cMledGeneQuiz,for large-scale biological sequence analysis. The system was designed to meet the needs that arise in computational seq...
Michael Scharf, Reinhard Schneider, Georg Casari, ...
This paper presents the Topic-Aspect Model (TAM), a Bayesian mixture model which jointly discovers topics and aspects. We broadly define an aspect of a document as a characteristi...