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» Prediction of Contact Maps Using Support Vector Machines
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BMCBI
2007
95views more  BMCBI 2007»
13 years 8 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
ICASSP
2011
IEEE
13 years 7 days ago
Structural MAP adaptation in GMM-supervector based speaker recognition
In recent years, adaptation techniques have been given special focus in speaker recognition tasks, mainly targeting speaker and session variation disentangling under the Maximum a...
Marc Ferras, Koichi Shinoda, Sadaoki Furui
CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 8 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
ICIP
2008
IEEE
14 years 10 months ago
Statistical learning based intra prediction in H.264
In this paper, we improve the performance of intra prediction and simplify mode decision procedure at the same time. For these works, we apply a statistical learning method such a...
Cheolhong An, Truong Q. Nguyen
BMCBI
2008
146views more  BMCBI 2008»
13 years 8 months ago
ProLoc-GO: Utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization
Background: Gene Ontology (GO) annotation, which describes the function of genes and gene products across species, has recently been used to predict protein subcellular and subnuc...
Wen-Lin Huang, Chun-Wei Tung, Shih-Wen Ho, Shiow-F...