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» Models for Incomplete and Probabilistic Information
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ISCI
2008
181views more  ISCI 2008»
15 years 4 months ago
Attribute reduction in decision-theoretic rough set models
Rough set theory can be applied to rule induction. There are two different types of classification rules, positive and boundary rules, leading to different decisions and consequen...
Yiyu Yao, Yan Zhao
MM
2003
ACM
132views Multimedia» more  MM 2003»
15 years 9 months ago
On image auto-annotation with latent space models
Image auto-annotation, i.e., the association of words to whole images, has attracted considerable attention. In particular, unsupervised, probabilistic latent variable models of t...
Florent Monay, Daniel Gatica-Perez
CEC
2009
IEEE
15 years 9 months ago
A novel EDAs based method for HP model protein folding
— The protein structure prediction (PSP) problem is one of the most important problems in computational biology. This paper proposes a novel Estimation of Distribution Algorithms...
Benhui Chen, Long Li, Jinglu Hu
FTML
2008
185views more  FTML 2008»
15 years 4 months ago
Graphical Models, Exponential Families, and Variational Inference
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Martin J. Wainwright, Michael I. Jordan
ICMCS
2005
IEEE
123views Multimedia» more  ICMCS 2005»
15 years 10 months ago
Hidden Markov Model Based Weighted Likelihood Discriminant for Minimum Error Shape Classification
The goal of this communication is to present a weighted likelihood discriminant for minimum error shape classification. Different from traditional Maximum Likelihood (ML) methods...
Ninad Thakoor, Sungyong Jung, Jean Gao