The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Part...
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
In this paper, we consider the relationship between risksensitivity and information. Product estimators are introduced as a generalization of Maximum A Posteriori Probability (MAP...
Vahid Reza Ramezani, Steven I. Marcus, Michael C. ...
This paper proposes a novel method to detect flames in video by processing the data generated by an ordinary camera monitoring a scene. In addition to ordinary motion and color cl...