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ICML
2010
IEEE
15 years 7 months ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum
ADCM
2008
136views more  ADCM 2008»
15 years 6 months ago
Learning and approximation by Gaussians on Riemannian manifolds
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Gui-Bo Ye, Ding-Xuan Zhou
TSP
2010
15 years 1 months ago
Learning graphical models for hypothesis testing and classification
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
JIIS
2000
120views more  JIIS 2000»
15 years 6 months ago
Machine Learning for Intelligent Processing of Printed Documents
Abstract. A paper document processing system is an information system component which transforms information on printed or handwritten documents into a computer-revisable form. In ...
Floriana Esposito, Donato Malerba, Francesca A. Li...
CVPR
2004
IEEE
16 years 8 months ago
Value Directed Learning of Gestures and Facial Displays
This paper presents a method for learning decision theoretic models of facial expressions and gestures from video data. We consider that the meaning of a facial display or gesture...
Jesse Hoey, James J. Little