Recently, there has been an increased focus on modeling uncertainty by distributions. Suppose we wish to compute a function of a stream whose elements are samples drawn independen...
Abstract: In this study, we applied artificial neural network, implementing the backpropagation algorithm, for the prediction of the excitation and emission maxima of green fluores...
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
Many analysis and monitoring applications require the repeated execution of expensive modeling functions over streams of rapidly changing data. These applications can often be exp...