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» Learning the Structure of Linear Latent Variable Models
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NIPS
2008
13 years 9 months ago
Learning Hybrid Models for Image Annotation with Partially Labeled Data
Extensive labeled data for image annotation systems, which learn to assign class labels to image regions, is difficult to obtain. We explore a hybrid model framework for utilizing...
Xuming He, Richard S. Zemel
ISI
2007
Springer
14 years 1 months ago
An LDA-based Community Structure Discovery Approach for Large-Scale Social Networks
Abstract— Community discovery has drawn significant research interests among researchers from many disciplines for its increasing application in multiple, disparate areas, inclu...
Haizheng Zhang, Baojun Qiu, C. Lee Giles, Henry C....
ECCV
2000
Springer
14 years 9 months ago
Non-linear Bayesian Image Modelling
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
Christopher M. Bishop, John M. Winn
NIPS
2000
13 years 9 months ago
On Reversing Jensen's Inequality
Jensen's inequality is a powerful mathematical tool and one of the workhorses in statistical learning. Its applications therein include the EM algorithm, Bayesian estimation ...
Tony Jebara, Alex Pentland
TSP
2010
13 years 2 months ago
Gaussian multiresolution models: exploiting sparse Markov and covariance structure
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...