Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
This paper is concerned with the generalization ability of learning to rank algorithms for information retrieval (IR). We point out that the key for addressing the learning proble...
Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang...
Many applications in text and speech processing require the analysis of distributions of variable-length sequences. We recently introduced a general kernel framework, rational ker...
In data mining, the selection of an appropriate classifier to estimate the value of an unknown attribute for a new instance has an essential impact to the quality of the classifica...
Automata models of learning systems introduced in the 1960s were popularized as learning automata (LA) in a survey paper in 1974 [1]. Since then, there have been many fundamental a...