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CORR
2007
Springer
167views Education» more  CORR 2007»
15 years 3 months ago
Optimal Solutions for Sparse Principal Component Analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonze...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
163
Voted
TCSV
2008
177views more  TCSV 2008»
15 years 3 months ago
An ICA Mixture Hidden Markov Model for Video Content Analysis
In this paper, a new theoretical framework based on hidden Markov model (HMM) and independent component analysis (ICA) mixture model is presented for content analysis of video, nam...
Jian Zhou, Xiao-Ping Zhang
ICML
2004
IEEE
16 years 4 months ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
GECCO
2005
Springer
232views Optimization» more  GECCO 2005»
15 years 9 months ago
Factorial representations to generate arbitrary search distributions
A powerful approach to search is to try to learn a distribution of good solutions (in particular of the dependencies between their variables) and use this distribution as a basis ...
Marc Toussaint
109
Voted
DGO
2008
126views Education» more  DGO 2008»
15 years 5 months ago
Active learning for e-rulemaking: public comment categorization
We address the e-rulemaking problem of reducing the manual labor required to analyze public comment sets. In current and previous work, for example, text categorization techniques...
Stephen Purpura, Claire Cardie, Jesse Simons