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GECCO
2009
Springer
101views Optimization» more  GECCO 2009»
15 years 4 months ago
Modeling UCS as a mixture of experts
We present a probabilistic formulation of UCS (a sUpervised Classifier System). UCS is shown to be a special case of mixture of experts where the experts are learned independentl...
Narayanan Unny Edakunni, Tim Kovacs, Gavin Brown, ...
WWW
2007
ACM
15 years 10 months ago
Topic sentiment mixture: modeling facets and opinions in weblogs
In this paper, we define the problem of topic-sentiment analysis on Weblogs and propose a novel probabilistic model to capture the mixture of topics and sentiments simultaneously....
Qiaozhu Mei, Xu Ling, Matthew Wondra, Hang Su, Che...
ICCV
2009
IEEE
16 years 2 months ago
Deformable Model Fitting with a Mixture of Local Experts
Local experts have been used to great effect for fitting deformable models to images. Typically, the best location in an image for the deformable model’s landmarks are found t...
Jason M. Saragih, Simon Lucey, Jeffrey F. Cohn
GECCO
2011
Springer
236views Optimization» more  GECCO 2011»
14 years 1 months ago
Online, GA based mixture of experts: a probabilistic model of ucs
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs
SIGIR
2006
ACM
15 years 3 months ago
Regularized estimation of mixture models for robust pseudo-relevance feedback
Pseudo-relevance feedback has proven to be an effective strategy for improving retrieval accuracy in all retrieval models. However the performance of existing pseudo feedback meth...
Tao Tao, ChengXiang Zhai