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ICMCS
2005
IEEE
284views Multimedia» more  ICMCS 2005»
14 years 3 months ago
Conditionally Positive Definite Kernels for SVM Based Image Recognition
Kernel based methods such as Support Vector Machine (SVM) have provided successful tools for solving many recognition problems. One of the reason of this success is the use of ker...
Sabri Boughorbel, Jean-Philippe Tarel, Nozha Bouje...
BICOB
2010
Springer
13 years 8 months ago
Multiple Kernel Learning for Fold Recognition
Fold recognition is a key problem in computational biology that involves classifying protein sharing structural similarities into classes commonly known as "folds". Rece...
Huzefa Rangwala
JMLR
2010
206views more  JMLR 2010»
13 years 4 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
PR
2006
93views more  PR 2006»
13 years 9 months ago
Learning the kernel parameters in kernel minimum distance classifier
Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods because the values of these parameters have significant impact on the per...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
SODA
2003
ACM
121views Algorithms» more  SODA 2003»
13 years 11 months ago
An improved approximation algorithm for the partial latin square extension problem
Previous work on the partial Latin square extension (PLSE) problem resulted in a 2-approximation algorithm based on the LP relaxation of a three-dimensional assignment IP formulat...
Carla P. Gomes, Rommel G. Regis, David B. Shmoys