"This course will consist of a number of major sections. The first will be a short review of some preliminary material, including asymptotics, summations, and recurrences and ...
We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...
This paper studies the aggregation of predictions made by tree-based models for several perturbed versions of the attribute vector of a test case. A closed-form approximation of t...
This paper describes a parameter estimation method for multi-label classification that does not rely on approximate inference. It is known that multi-label classification involvin...
Abstract. In this paper, motivated by applications of ordinary (distance) spanners in communication networks and to address such issues as bandwidth constraints on network links, l...