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» Learning Probabilistic Models of Relational Structure
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SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
15 years 1 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
106
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TMI
2011
147views more  TMI 2011»
14 years 7 months ago
Labeling of Lumbar Discs Using Both Pixel- and Object-Level Features With a Two-Level Probabilistic Model
Abstract—Backbone anatomical structure detection and labeling is a necessary step for various analysis tasks of the vertebral column. Appearance, shape and geometry measurements ...
Raja' S. Alomari, Jason J. Corso, Vipin Chaudhary
CVPR
2010
IEEE
15 years 5 months ago
Novel Observation Model for Probabilistic Object Tracking
Treating visual object tracking as foreground and background classification problem has attracted much attention in the past decade. Most methods adopt mean shift or brute force s...
Dawei Liang, Qingming Huang, Hongxun Yao, Shuqiang...
125
Voted
ACL
2009
14 years 10 months ago
Distant supervision for relation extraction without labeled data
Modern models of relation extraction for tasks like ACE are based on supervised learning of relations from small hand-labeled corpora. We investigate an alternative paradigm that ...
Mike Mintz, Steven Bills, Rion Snow, Daniel Jurafs...
116
Voted
EMNLP
2011
14 years 7 days ago
Lexical Generalization in CCG Grammar Induction for Semantic Parsing
We consider the problem of learning factored probabilistic CCG grammars for semantic parsing from data containing sentences paired with logical-form meaning representations. Tradi...
Tom Kwiatkowski, Luke S. Zettlemoyer, Sharon Goldw...