We consider the question of why modern machine learning methods like support vector machines outperform earlier nonparametric techniques like kNN. Our approach investigates the lo...
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn ho...
Abstract— Meta-learning helps us find solutions to computational intelligence (CI) challenges in automated way. Metalearning algorithm presented in this paper is universal and m...
The Biased Minimax Probability Machine (BMPM) constructs a classifier which deals with the imbalanced learning tasks. In this paper, we propose a Second Order Cone Programming (SO...
Abstract. We propose a machine learning approach to action prediction in oneshot games. In contrast to the huge literature on learning in games where an agent's model is deduc...