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AAAI
2012
11 years 10 months ago
Learning the Kernel Matrix with Low-Rank Multiplicative Shaping
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
Tomer Levinboim, Fei Sha
ICML
2005
IEEE
14 years 8 months ago
Preference learning with Gaussian processes
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
Wei Chu, Zoubin Ghahramani
ICML
2008
IEEE
14 years 8 months ago
Composite kernel learning
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
Marie Szafranski, Yves Grandvalet, Alain Rakotomam...
ACCV
2006
Springer
13 years 9 months ago
Learning Multi-category Classification in Bayesian Framework
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
Atul Kanaujia, Dimitris N. Metaxas
JMLR
2006
156views more  JMLR 2006»
13 years 7 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...