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TNN
2010
234views Management» more  TNN 2010»
13 years 14 days ago
Novel maximum-margin training algorithms for supervised neural networks
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...
Oswaldo Ludwig, Urbano Nunes
NIPS
2008
13 years 7 months ago
Continuously-adaptive discretization for message-passing algorithms
Continuously-Adaptive Discretization for Message-Passing (CAD-MP) is a new message-passing algorithm for approximate inference. Most message-passing algorithms approximate continu...
Michael Isard, John MacCormick, Kannan Achan
ATAL
2008
Springer
13 years 7 months ago
A tractable and expressive class of marginal contribution nets and its applications
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...
SDM
2009
SIAM
152views Data Mining» more  SDM 2009»
14 years 2 months ago
Multiple Kernel Clustering.
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...
Bin Zhao, James T. Kwok, Changshui Zhang
NIPS
2007
13 years 7 months ago
A Risk Minimization Principle for a Class of Parzen Estimators
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 ...