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BMCBI
2007
178views more  BMCBI 2007»
15 years 6 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
ECCV
2006
Springer
16 years 8 months ago
Studying Aesthetics in Photographic Images Using a Computational Approach
Aesthetics, in the world of art and photography, refers to the principles of the nature and appreciation of beauty. Judging beauty and other aesthetic qualities of photographs is a...
Ritendra Datta, Dhiraj Joshi, Jia Li, James Ze Wan...
IPMI
2003
Springer
16 years 7 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...
ICML
2008
IEEE
16 years 7 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
2004
IEEE
16 years 7 months ago
Improving SVM accuracy by training on auxiliary data sources
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
Pengcheng Wu, Thomas G. Dietterich