This paper proposes a general learning framework for a class of problems that require learning over latent intermediate representations. Many natural language processing (NLP) dec...
Ming-Wei Chang, Dan Goldwasser, Dan Roth, Vivek Sr...
We consider a generalization of stochastic bandit problems where the set of arms, X, is allowed to be a generic topological space. We constraint the mean-payoff function with a di...
Abstract. We prove a weak version of the dynamic programming principle for standard stochastic control problems and mixed control-stopping problems, which avoids the technical diļ¬...
Data sets resulting from physical simulations typically contain a multitude of physical variables. It is, therefore, desirable that visualization methods take into account the enti...
Lars Linsen, Tran Van Long, Paul Rosenthal, Ste...
Large amounts of remotely sensed data calls for data mining techniques to fully utilize their rich information content. In this paper, we study new means of discovery and summariz...