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» Learning Relations Using Collocations
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118
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ML
2002
ACM
146views Machine Learning» more  ML 2002»
15 years 2 months ago
Kernel Matching Pursuit
Matching Pursuit algorithms learn a function that is a weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target fu...
Pascal Vincent, Yoshua Bengio
128
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ICML
2004
IEEE
16 years 3 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
100
Voted
ICCAD
2002
IEEE
146views Hardware» more  ICCAD 2002»
15 years 11 months ago
Conflict driven learning in a quantified Boolean Satisfiability solver
Within the verification community, there has been a recent increase in interest in Quantified Boolean Formula evaluation (QBF) as many interesting sequential circuit verification ...
Lintao Zhang, Sharad Malik
120
Voted
HICSS
2008
IEEE
147views Biometrics» more  HICSS 2008»
15 years 9 months ago
Can Peer-to-Peer Networks Facilitate Information Sharing in Collaborative Learning?
Many peer-to-peer (P2P) networks have been widely used for file sharing. A peer acts both as a content provider and a consumer, and is granted autonomy to decide what content, wit...
Fu-ren Lin, Sheng-cheng Lin, Ying-fen Wang
ICDM
2007
IEEE
187views Data Mining» more  ICDM 2007»
15 years 8 months ago
A Comparative Study of Methods for Transductive Transfer Learning
The problem of transfer learning, where information gained in one learning task is used to improve performance in another related task, is an important new area of research. While...
Andrew Arnold, Ramesh Nallapati, William W. Cohen