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...
This paper proposes a hybrid of handcrafted rules and a machine learning method for chunking Korean. In the partially free word-order languages such as Korean and Japanese, a smal...