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» Regularized Learning with Networks of Features
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PAMI
2002
112views more  PAMI 2002»
14 years 11 months ago
Recognizing Handwritten Digits Using Hierarchical Products of Experts
The product of experts learning procedure [1] can discover a set of stochastic binary features that constitute a nonlinear generative model of handwritten images of digits. The qua...
Guy Mayraz, Geoffrey E. Hinton
AI
2006
Springer
14 years 12 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
INFORMS
1998
100views more  INFORMS 1998»
14 years 11 months ago
Feature Selection via Mathematical Programming
The problem of discriminating between two nite point sets in n-dimensional feature space by a separating plane that utilizes as few of the features as possible, is formulated as a...
Paul S. Bradley, Olvi L. Mangasarian, W. Nick Stre...
ICANN
2009
Springer
15 years 4 months ago
Empirical Study of the Universum SVM Learning for High-Dimensional Data
Abstract. Many applications of machine learning involve sparse highdimensional data, where the number of input features is (much) larger than the number of data samples, d n. Predi...
Vladimir Cherkassky, Wuyang Dai
ICDM
2009
IEEE
183views Data Mining» more  ICDM 2009»
14 years 9 months ago
Multirelational Topic Models
In this paper we propose the multirelational topic model (MRTM) for multiple types of link modeling such as citation and coauthor links in document networks. In the citation networ...
Jia Zeng, William K. Cheung, Chun-hung Li, Jiming ...