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COLT
2004
Springer
13 years 10 months ago
Performance Guarantees for Regularized Maximum Entropy Density Estimation
Abstract. We consider the problem of estimating an unknown probability distribution from samples using the principle of maximum entropy (maxent). To alleviate overfitting with a v...
Miroslav Dudík, Steven J. Phillips, Robert ...
ICML
2003
IEEE
14 years 5 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...
ACML
2009
Springer
13 years 11 months ago
Robust Discriminant Analysis Based on Nonparametric Maximum Entropy
In this paper, we propose a Robust Discriminant Analysis based on maximum entropy (MaxEnt) criterion (MaxEnt-RDA), which is derived from a nonparametric estimate of Renyi’s quadr...
Ran He, Bao-Gang Hu, Xiaotong Yuan
PAMI
2006
114views more  PAMI 2006»
13 years 4 months ago
Nonparametric Supervised Learning by Linear Interpolation with Maximum Entropy
Nonparametric neighborhood methods for learning entail estimation of class conditional probabilities based on relative frequencies of samples that are "near-neighbors" of...
Maya R. Gupta, Robert M. Gray, Richard A. Olshen
IWANN
2001
Springer
13 years 9 months ago
Pattern Repulsion Revisited
Marques and Almeida [9] recently proposed a nonlinear data seperation technique based on the maximum entropy principle of Bell and Sejnowsky. The idea behind is a pattern repulsion...
Fabian J. Theis, Christoph Bauer, Carlos Garc&iacu...