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» Learning from Highly Structured Data by Decomposition
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CVPR
2003
IEEE
15 years 12 months ago
Learning Object Intrinsic Structure for Robust Visual Tracking
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
Qiang Wang, Guangyou Xu, Haizhou Ai
CVPR
2007
IEEE
15 years 12 months ago
Learning GMRF Structures for Spatial Priors
The goal of this paper is to find sparse and representative spatial priors that can be applied to part-based object localization. Assuming a GMRF prior over part configurations, w...
Lie Gu, Eric P. Xing, Takeo Kanade
UAI
1996
14 years 11 months ago
Learning Equivalence Classes of Bayesian Network Structures
Two Bayesian-network structures are said to be equivalent if the set of distributions that can be represented with one of those structures is identical to the set of distributions...
David Maxwell Chickering
ICML
2009
IEEE
15 years 10 months ago
Learning Markov logic network structure via hypergraph lifting
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
Stanley Kok, Pedro Domingos
AIRWEB
2009
Springer
15 years 4 months ago
Tag spam creates large non-giant connected components
Spammers in social bookmarking systems try to mimick bookmarking behaviour of real users to gain the attention of other users or search engines. Several methods have been proposed...
Nicolas Neubauer, Robert Wetzker, Klaus Obermayer