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BMCBI
2007
178views more  BMCBI 2007»
15 years 3 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
111
Voted
ICIP
2008
IEEE
16 years 5 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...
IPMI
2003
Springer
16 years 4 months ago
Feature Selection for Shape-Based Classification of Biological Objects
Abstract. In this paper, feature selection methodology from the machine learning literature is applied to the problem of shape-based classification. This methodology discards stati...
Paul A. Yushkevich, Sarang C. Joshi, Stephen M. Pi...
120
Voted
ICML
2008
IEEE
16 years 4 months ago
Localized multiple kernel learning
Recently, instead of selecting a single kernel, multiple kernel learning (MKL) has been proposed which uses a convex combination of kernels, where the weight of each kernel is opt...
Ethem Alpaydin, Mehmet Gönen
ICML
2005
IEEE
16 years 4 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...