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» Incremental and Decremental Support Vector Machine Learning
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ECML
2006
Springer
15 years 1 months ago
Sequence Discrimination Using Phase-Type Distributions
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
Jérôme Callut, Pierre Dupont
ICAISC
2004
Springer
15 years 3 months ago
Relevance LVQ versus SVM
Abstract. The support vector machine (SVM) constitutes one of the most successful current learning algorithms with excellent classification accuracy in large real-life problems an...
Barbara Hammer, Marc Strickert, Thomas Villmann
BMCBI
2007
95views more  BMCBI 2007»
14 years 10 months ago
Phylogenetic tree information aids supervised learning for predicting protein-protein interaction based on distance matrices
Background: Protein-protein interactions are critical for cellular functions. Recently developed computational approaches for predicting protein-protein interactions utilize co-ev...
Roger A. Craig, Li Liao
ML
2006
ACM
113views Machine Learning» more  ML 2006»
15 years 3 months ago
A separate compilation extension to standard ML
We present an extension to Standard ML, called SMLSC, to support separate compilation. The system gives meaning to individual program fragments, called units. Units may depend on ...
David Swasey, Tom Murphy VII, Karl Crary, Robert H...
ICPR
2008
IEEE
15 years 11 months ago
SVMs, Gaussian mixtures, and their generative/discriminative fusion
We present a new technique that employs support vector machines and Gaussian mixture densities to create a generative/discriminative joint classifier. In the past, several approac...
Georg Heigold, Hermann Ney, Thomas Deselaers