Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
We argue that in general, the analysis of lexical cohesion factors in a document can drive a summarizer, as well as enable other content characterization tasks. More narrowly, thi...
When aligning texts in very different languages such as Korean and English, structural features beyond word or phrase give useful intbrmation. In this paper, we present a method f...
This paper explores the increasing the heterogeneity of an agent population to stabilize decentralized systems by adding bias terms to each agent's expected payoffs. Two appr...
We propose a new approach to the problem of searching a space of policies for a Markov decision process (MDP) or a partially observable Markov decision process (POMDP), given a mo...