Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
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...
Abstract Trained musicians intuitively produce expressive variations that add to their audience's enjoyment. However, there is little quantitative information about the kinds ...
Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise,...
— The main objetive of this paper is to improve the current status of learning object search. First, the current situation is analyzed and a theretical solution, based on relevan...