We study a time series model that can be viewed as a decision tree with Markov temporal structure. The model is intractable for exact calculations, thus we utilize variational app...
Michael I. Jordan, Zoubin Ghahramani, Lawrence K. ...
We extend the Bayesian Information Criterion (BIC), an asymptotic approximation for the marginal likelihood, to Bayesian networks with hidden variables. This approximation can be ...
Relaxed Online Support Vector Machines (ROSVMs) have recently been proposed as an efficient methodology for attaining an approximate SVM solution for streaming data such as the on...
We investigate the sparse eigenvalue problem which arises in various fields such as machine learning and statistics. Unlike standard approaches relying on approximation of the l0n...
-- The optimal buffer allocation in queueing network systems is a difficult stochastic, non-linear, integer mathematical programming problem. Moreover, the objective function, the ...
Frederico R. B. Cruz, A. R. Duarte, Tom Van Woense...