We present a new approach for the discriminative training
of continuous-valued Markov Random Field (MRF)
model parameters. In our approach we train the MRF
model by optimizing t...
Abstract. In this paper we develop a localized value-ordering heuristic for distributed resource allocation problems. We show how this value ordering heuristics can be used to achi...
Developing scalable algorithms for solving partially observable Markov decision processes (POMDPs) is an important challenge. One promising approach is based on representing POMDP...
Christopher Amato, Daniel S. Bernstein, Shlomo Zil...
User preferences for automated assistance often vary widely, depending on the situation, and quality or presentation of help. Developing effective models to learn individual prefe...
This paper focuses on parallel query optimization. We consider the operator problem and introduce a new class of execution strategies called Linear-Oriented Bushy Trees (LBTs). Co...