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CIVR
2006
Springer
219views Image Analysis» more  CIVR 2006»
13 years 11 months ago
Bayesian Learning of Hierarchical Multinomial Mixture Models of Concepts for Automatic Image Annotation
We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...
Rui Shi, Tat-Seng Chua, Chin-Hui Lee, Sheng Gao
SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
12 years 10 months ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth
ICAPR
2005
Springer
14 years 1 months ago
Multi-view EM Algorithm for Finite Mixture Models
In this paper, Multi-View Expectation and Maximization algorithm for finite mixture models is proposed by us to handle realworld learning problems which have natural feature split...
Xing Yi, Yunpeng Xu, Changshui Zhang
CORR
2010
Springer
114views Education» more  CORR 2010»
13 years 7 months ago
Settling the Polynomial Learnability of Mixtures of Gaussians
Given data drawn from a mixture of multivariate Gaussians, a basic problem is to accurately estimate the mixture parameters. We give an algorithm for this problem that has running ...
Ankur Moitra, Gregory Valiant
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 8 months ago
A bayesian mixture model with linear regression mixing proportions
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...