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» Normalization in Support Vector Machines
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JMLR
2012
13 years 9 months ago
Max-Margin Min-Entropy Models
We propose a new family of latent variable models called max-margin min-entropy (m3e) models, which define a distribution over the output and the hidden variables conditioned on ...
Kevin Miller, M. Pawan Kumar, Benjamin Packer, Dan...
PRICAI
2000
Springer
15 years 10 months ago
A Comparative Study on Chinese Text Categorization Methods
Abstract. This paper reports our comparative evaluation of three machine learning methods on Chinese text categorization. Whereas a wide range of methods have been applied to Engli...
Ji He, Ah-Hwee Tan, Chew Lim Tan
CVPR
2010
IEEE
15 years 9 months ago
Large-Scale Image Categorization with Explicit Data Embedding
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Florent Perronnin, Jorge Sanchez, Yan Liu
ICML
2007
IEEE
16 years 7 months ago
Local similarity discriminant analysis
We propose a local, generative model for similarity-based classification. The method is applicable to the case that only pairwise similarities between samples are available. The c...
Luca Cazzanti, Maya R. Gupta
ICML
2008
IEEE
16 years 7 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...