The martingale framework for detecting changes in data stream, currently only applicable to labeled data, is extended here to unlabeled data using clustering concept. The one-pass...
Occam’s razor is the principle that, given two hypotheses consistent with the observed data, the simpler one should be preferred. Many machine learning algorithms follow this pr...
Dynamic programming algorithms provide a basic tool identifying optimal solutions in Markov Decision Processes (MDP). The paper develops a representation for decision diagrams sui...
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Caching, symmetries, and search with decomposition are powerful techniques for pruning the search space of constraint problems. In this paper we present an innovative way of effi...