We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
The adaptation of software technology to distributed environments is an important challenge today. In this work we combine parallel and distributed search. By this way we add the ...
Abstract. In this paper, we mainly explore the effectiveness of two kernelbased methods, the convolution tree kernel and the shortest path dependency kernel, for Chinese relation e...
This paper proposes a novel composite kernel for relation extraction. The composite kernel consists of two individual kernels: an entity kernel that allows for entity-related feat...
Nearest neighbour search is a widely used technique in pattern recognition. During the last three decades a large number of fast algorithms have been proposed. In this work we are...