This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Continuously-Adaptive Discretization for Message-Passing (CAD-MP) is a new message-passing algorithm for approximate inference. Most message-passing algorithms approximate continu...
Coalitional games raise a number of important questions from the point of view of computer science, key among them being how to represent such games compactly, and how to efficien...
Edith Elkind, Leslie Ann Goldberg, Paul W. Goldber...
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
This paper1 explores the use of a Maximal Average Margin (MAM) optimality principle for the design of learning algorithms. It is shown that the application of this risk minimizati...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...