Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
We introduce novel algorithms for generating random solutions from a uniform distribution over the solutions of a boolean satisfiability problem. Our algorithms operate in two pha...
We present an extension of the Dynamics Based Control (DBC) paradigm to environment models based on Predictive State Representations (PSRs). We show an approximate greedy version ...
Ariel Adam, Zinovi Rabinovich, Jeffrey S. Rosensch...
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
This paper proposes a new planning architecture for agents operating in uncertain and dynamic environments. Decisiontheoretic planning has been recognized as a useful tool for rea...