This paper re-examines the problem of parameter estimation in Bayesian networks with missing values and hidden variables from the perspective of recent work in on-line learning [1...
Consider the problem of joint parameter estimation and prediction in a Markov random field: i.e., the model parameters are estimated on the basis of an initial set of data, and th...
Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing ...
Helge Langseth, Thomas D. Nielsen, Rafael Rum&iacu...
The number of active users, their timing offsets, and their (possibly dispersive) channels with the access point are decisive parameters for wireless code division multiple access...
Daniele Angelosante, Emanuele Grossi, Georgios B. ...
Niching is an important technique for multimodal optimization. Most existing niching methods require specification of certain niching parameters in order to perform well. These nic...