Various problems in machine learning, databases, and statistics involve pairwise distances among a set of objects. It is often desirable for these distances to satisfy the propert...
Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem, we propose the E...
Prioritized sweeping is a model-based reinforcement learning method that attempts to focus an agent’s limited computational resources to achieve a good estimate of the value of ...
Learning how to make decisions in a domain is a critical aspect of intelligent planning behavior. The ability of a planner to adapt its decision-making to a domain depends in part...
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...