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» Learning with Rigorous Support Vector Machines
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COLT
2003
Springer
15 years 9 months ago
Learning from Uncertain Data
The application of statistical methods to natural language processing has been remarkably successful over the past two decades. But, to deal with recent problems arising in this ï¬...
Mehryar Mohri
165
Voted
JMLR
2006
186views more  JMLR 2006»
15 years 3 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
WWW
2004
ACM
16 years 4 months ago
Web image learning for searching semantic concepts in image databases
Without textual descriptions or label information of images, searching semantic concepts in image databases is still a very challenging task. While automatic annotation techniques...
Chu-Hong Hoi, Michael R. Lyu
CIKM
2005
Springer
15 years 9 months ago
Discretization based learning approach to information retrieval
We approached the problem as learning how to order documents by estimated relevance with respect to a user query. Our support vector machines based classifier learns from the rele...
Dmitri Roussinov, Weiguo Fan, Fernando A. Das Neve...
138
Voted
PAMI
2008
302views more  PAMI 2008»
15 years 3 months ago
Learning to Detect Moving Shadows in Dynamic Environments
We propose a novel adaptive technique for detecting moving shadows and distinguishing them from moving objects in video sequences. Most methods for detecting shadows work in a stat...
Ajay J. Joshi, Nikolaos Papanikolopoulos