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JMLR
2008
114views more  JMLR 2008»
14 years 9 months ago
Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
AAAI
2008
15 years 1 days ago
Markov Blanket Feature Selection for Support Vector Machines
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
Jianqiang Shen, Lida Li, Weng-Keen Wong
BIOCOMP
2006
14 years 11 months ago
Support Vector Machines for Predicting microRNA Hairpins
- microRNAs (miRNAs) are 20-22 nt noncoding RNAs which are rapidly emerging as crucial regulators of gene expression in plants and animals. Identification of the hairpins which yie...
Karol Szafranski, Molly Megraw, Martin Reczko, Art...
TSP
2008
180views more  TSP 2008»
14 years 9 months ago
Support Vector Machine Training for Improved Hidden Markov Modeling
We present a discriminative training algorithm, that uses support vector machines (SVMs), to improve the classification of discrete and continuous output probability hidden Markov ...
Alba Sloin, David Burshtein
TSD
2010
Springer
14 years 7 months ago
Correlation Features and a Linear Transform Specific Reproducing Kernel
Abstract. In this paper we introduce two ideas for phoneme classification: First, we derive the necessary steps to integrate linear transform into the computation of reproducing ke...
Andreas Beschorner, Dietrich Klakow