Abstract. A conditioning graph (CG) is a graphical structure that attempt to minimize the implementation overhead of computing probabilities in belief networks. A conditioning grap...
We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled a...
Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Gre...
Optimality conditions are derived for problems of minimizing a general measure of deviation of a random variable, with special attention to situations where the random variable cou...
R. Tyrrell Rockafellar, Stan Uryasev, Michael Zaba...
We introduce an expectation maximizationtype (EM) algorithm for maximum likelihood optimization of conditional densities. It is applicable to hidden variable models where the dist...
—In this paper we describe a prototype system of identifying environment condition utilizing signals emitted by people. Many people move around in many places such as urban and m...