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ICPR
2008
IEEE
16 years 1 months ago
A fast revised simplex method for SVM training
Active set methods for training the Support Vector Machines (SVM) are advantageous since they enable incremental training and, as we show in this research, do not exhibit exponent...
Christopher Sentelle, Georgios C. Anagnostopoulos,...
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ICPR
2010
IEEE
16 years 2 days ago
2D Shape Recognition Using Information Theoretic Kernels
In this paper, a novel approach for contour-based 2D shape recognition is proposed, using a recently introduced class of information theoretic kernels. This kind of kernels, based...
Manuele Bicego, André Filipe Torres Martins, Vitt...
BICOB
2009
Springer
15 years 10 months ago
Constrained Fisher Scores Derived from Interaction Profile Hidden Markov Models Improve Protein to Protein Interaction Predictio
Protein-protein interaction plays critical roles in cellular functions. In this work, we propose a computational method to predict protein-protein interaction by using support vec...
Alvaro J. González, Li Liao
DIS
2008
Springer
15 years 8 months ago
String Kernels Based on Variable-Length-Don't-Care Patterns
Abstract. We propose a new string kernel based on variable-lengthdon't-care patterns (VLDC patterns). A VLDC pattern is an element of ({}) , where is an alphabet and is the ...
Kazuyuki Narisawa, Hideo Bannai, Kohei Hatano, Shu...
NECO
2010
101views more  NECO 2010»
15 years 1 months ago
Large-Margin Classification in Infinite Neural Networks
We introduce a new family of positive-definite kernels for large margin classification in support vector machines (SVMs). These kernels mimic the computation in large neural netwo...
Youngmin Cho, Lawrence K. Saul