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» Support Kernel Machines for Object Recognition
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PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
15 years 4 months ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
DAGM
2004
Springer
15 years 3 months ago
Learning with Distance Substitution Kernels
Abstract. During recent years much effort has been spent in incorporating problem specific a-priori knowledge into kernel methods for machine learning. A common example is a-prior...
Bernard Haasdonk, Claus Bahlmann
MMM
2005
Springer
202views Multimedia» more  MMM 2005»
15 years 3 months ago
Image Mining and Retrieval Using Hierarchical Support Vector Machines
For some time now, image retrieval approaches have been developed that use low-level features, such as colour histograms, edge distributions and texture measures. What has been la...
Ross Brown, Binh Pham
CONEXT
2007
ACM
14 years 11 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek
ICPR
2010
IEEE
14 years 7 months ago
Learning the Kernel Combination for Object Categorization
Although Support Vector Machines(SVM) succeed in classifying several image databases using image descriptors proposed in the literature, no single descriptor can be optimal for ge...
Deyuan Zhang, Xiaolong Wang, Bingquan Liu