In a trend that reflects the increasing demand for intelligent applications driven by business data, IBM today is building out a significant number of applications that leverage m...
This paper presents an updated version of the adaptive learning particle swarm optimizer (ALPSO) [6], we call it ALPSO-II. In order to improve the performance of ALPSO on multi-mod...
We describe a novel framework for the design and analysis of online learning algorithms based on the notion of duality in constrained optimization. We cast a sub-family of universa...
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
: Sequential algorithms given by Angluin 1987 and Schapire 1992 learn deterministic nite automata DFA exactly from Membership and Equivalence queries. These algorithms are feasible...