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» Incremental and Decremental Support Vector Machine Learning
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JMLR
2002
115views more  JMLR 2002»
14 years 9 months ago
PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Matthias Seeger
ICIP
2008
IEEE
15 years 11 months ago
Recovering wavelet relations using SVM for image denoising
Here we propose an alternative non-explicit way to take into account the relations among wavelet coefficients in natural images for denoising: we use Support Vector Machines (SVM)...
Valero Laparra, Juan Gutierrez, Gustavo Camps-Vall...
ICML
2005
IEEE
15 years 10 months ago
Large scale genomic sequence SVM classifiers
In genomic sequence analysis tasks like splice site recognition or promoter identification, large amounts of training sequences are available, and indeed needed to achieve suffici...
Bernhard Schölkopf, Gunnar Rätsch, S&oum...
ICMCS
2006
IEEE
125views Multimedia» more  ICMCS 2006»
15 years 3 months ago
Label Disambiguation and Sequence Modeling for Identifying Human Activities from Wearable Physiological Sensors
Wearable physiological sensors can provide a faithful record of a patient’s physiological states without constant attention of caregivers. A computer program that can infer huma...
Wei-Hao Lin, Alexander G. Hauptmann
JMM2
2006
218views more  JMM2 2006»
14 years 9 months ago
Automatic Recognition of Facial Actions in Spontaneous Expressions
Spontaneous facial expressions differ from posed expressions in both which muscles are moved, and in the dynamics of the movement. Advances in the field of automatic facial express...
Marian Stewart Bartlett, Gwen Littlewort, Mark G. ...