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TNN
2008
182views more  TNN 2008»
13 years 7 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...
RECOMB
2007
Springer
14 years 8 months ago
Support Vector Training of Protein Alignment Models
Abstract. Sequence to structure alignment is an important step in homology modeling of protein structures. Incorporation of features like secondary structure, solvent accessibility...
Chun-Nam John Yu, Thorsten Joachims, Ron Elber, Ja...
ACL
2010
13 years 5 months ago
A Study of Information Retrieval Weighting Schemes for Sentiment Analysis
Most sentiment analysis approaches use as baseline a support vector machines (SVM) classifier with binary unigram weights. In this paper, we explore whether more sophisticated fea...
Georgios Paltoglou, Mike Thelwall
ICMCS
2005
IEEE
148views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Facial Expression Recognition with Relevance Vector Machines
For many decades automatic facial expression recognition has scientifically been considered a real challenging problem in the fields of pattern recognition or robotic vision. The ...
Dragos Datcu, Léon J. M. Rothkrantz
ICASSP
2008
IEEE
14 years 2 months ago
Nonparametric feature normalization for SVM-based speaker verification
We investigate several feature normalization and scaling approaches for use in speaker verification based on support vector machines. We are particularly interested in methods th...
Andreas Stolcke, Sachin S. Kajarekar, Luciana Ferr...