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UAI
2000
14 years 11 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
TNN
2008
182views more  TNN 2008»
14 years 9 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
BMCBI
2010
130views more  BMCBI 2010»
14 years 10 months ago
Amino acid "little Big Bang": Representing amino acid substitution matrices as dot products of Euclidian vectors
Background: Sequence comparisons make use of a one-letter representation for amino acids, the necessary quantitative information being supplied by the substitution matrices. This ...
Karel Zimmermann, Jean-François Gibrat
NIPS
2001
14 years 11 months ago
A Sequence Kernel and its Application to Speaker Recognition
A novel approach for comparing sequences of observations using an explicit-expansion kernel is demonstrated. The kernel is derived using the assumption of the independence of the ...
W. M. Campbell
IJCNN
2008
IEEE
15 years 4 months ago
Ranking and selecting clustering algorithms using a meta-learning approach
Abstract— We present a novel framework that applies a metalearning approach to clustering algorithms. Given a dataset, our meta-learning approach provides a ranking for the candi...
Marcílio Carlos Pereira de Souto, Ricardo B...