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» Learning of Boolean Functions Using Support Vector Machines
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ICPR
2010
IEEE
13 years 6 months ago
Incremental Training of Multiclass Support Vector Machines
We present a new method for the incremental training of multiclass Support Vector Machines that provides computational efficiency for training problems in the case where the trai...
Symeon Nikitidis, Nikos Nikolaidis, Ioannis Pitas
RECOMB
2002
Springer
14 years 8 months ago
Combining pairwise sequence similarity and support vector machines for remote protein homology detection
One key element in understanding the molecular machinery of the cell is to understand the meaning, or function, of each protein encoded in the genome. A very successful means of i...
Li Liao, William Stafford Noble
ICML
2008
IEEE
14 years 8 months ago
Stopping conditions for exact computation of leave-one-out error in support vector machines
We propose a new stopping condition for a Support Vector Machine (SVM) solver which precisely reflects the objective of the Leave-OneOut error computation. The stopping condition ...
Klaus-Robert Müller, Pavel Laskov, Vojtech Fr...
ML
2002
ACM
220views Machine Learning» more  ML 2002»
13 years 7 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
SDM
2007
SIAM
81views Data Mining» more  SDM 2007»
13 years 9 months ago
A PAC Bound for Approximate Support Vector Machines
We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...
Dongwei Cao, Daniel Boley