In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Background: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heteroge...
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
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...
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...