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» On learning algorithm selection for classification
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115
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ICML
2008
IEEE
16 years 1 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray
SEMWEB
2007
Springer
15 years 6 months ago
Optimizing the Retrieval of Pertinent Answers for NL Questions with the E-Librarian Service
Abstract. There is a growing discrepancy between the creation of digital content and its actual employment and usefulness in a learning society. Technologies for recording lectures...
Serge Linckels, Harald Sack, Christoph Meinel
96
Voted
CIKM
2011
Springer
14 years 18 days ago
Toward interactive training and evaluation
Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...
Gregory Druck, Andrew McCallum
162
Voted

Publication
151views
13 years 4 months ago
Can faces verify blood-relations?
Humans can verify unknown parent-offspring and sibling pairs over unrelated subject pairs. A computational scheme to accomplish the task robustly, in the presence of challenges due...
Gowri Somanath, Chandra Kambhamettu
106
Voted
CVPR
2001
IEEE
16 years 2 months ago
Bayesian Color Constancy for Outdoor Object Recognition
Outdoor scene classification is challenging due to irregular geometry, uncontrolled illumination, and noisy reflectance distributions. This paper discusses a Bayesian approach to ...
Yanghai Tsin, Robert T. Collins, Visvanathan Rames...