Probably approximately correct learning

Results: 61



#Item
31A Discriminative Model for Semi-Supervised Learning ∗ Maria-Florina Balcan School of Computer Science, Georgia Institute of Technology Avrim Blum Computer Science Department, Carnegie Mellon University

A Discriminative Model for Semi-Supervised Learning ∗ Maria-Florina Balcan School of Computer Science, Georgia Institute of Technology Avrim Blum Computer Science Department, Carnegie Mellon University

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Source URL: www.cs.cmu.edu

Language: English - Date: 2009-09-02 22:40:44
32JMLR: Workshop and Conference Proceedings vol[removed]–22  Distributed Learning, Communication Complexity and Privacy Maria-Florina Balcan∗

JMLR: Workshop and Conference Proceedings vol[removed]–22 Distributed Learning, Communication Complexity and Privacy Maria-Florina Balcan∗

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Source URL: www.cs.cmu.edu

Language: English - Date: 2012-06-04 16:01:05
33JMLR: Workshop and Conference Proceedings vol[removed]–34  Robust Interactive Learning Maria Florina Balcan  NINAMF @ CC . GATECH . EDU

JMLR: Workshop and Conference Proceedings vol[removed]–34 Robust Interactive Learning Maria Florina Balcan NINAMF @ CC . GATECH . EDU

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Source URL: www.cs.cmu.edu

Language: English - Date: 2012-05-24 20:13:01
34PAC Subset Selection in Stochastic Multi-armed Bandits

PAC Subset Selection in Stochastic Multi-armed Bandits

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Source URL: icml.cc

Language: English - Date: 2012-06-07 13:20:18
35Hybrid hierarchical steps and learning by abstraction for an emotion recognition system  BRUNO APOLLONI, CHRISTOS OROVAS, GIORGIO PALMAS Computer Science Department, University of Milan Via Comelico 39, 20 135, ITALY

Hybrid hierarchical steps and learning by abstraction for an emotion recognition system  BRUNO APOLLONI, CHRISTOS OROVAS, GIORGIO PALMAS Computer Science Department, University of Milan Via Comelico 39, 20 135, ITALY

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Source URL: www.image.ece.ntua.gr

Language: English - Date: 2000-10-25 10:59:02
36Characterizing the Sample Complexity of Private Learners∗ Amos Beimel Kobbi Nissim  Uri Stemmer

Characterizing the Sample Complexity of Private Learners∗ Amos Beimel Kobbi Nissim Uri Stemmer

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Source URL: privacytools.seas.harvard.edu

Language: English - Date: 2014-07-01 20:06:57
37LNCS[removed]Private Learning and Sanitization: Pure vs. Approximate Differential Privacy

LNCS[removed]Private Learning and Sanitization: Pure vs. Approximate Differential Privacy

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Source URL: privacytools.seas.harvard.edu

Language: English - Date: 2014-07-01 16:31:39
38Incorporating Prior Domain Knowledge Into Inductive Supervised Machine Learning  Incorporating Prior Domain Knowledge Into Inductive Machine Learning Ting Yu Tony Jan

Incorporating Prior Domain Knowledge Into Inductive Supervised Machine Learning Incorporating Prior Domain Knowledge Into Inductive Machine Learning Ting Yu Tony Jan

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Source URL: forecasters.org

Language: English - Date: 2008-07-28 10:30:24
39Journal of Machine Learning Research[removed]1460  Submitted 5/06; Revised 10/06; Published 7/07 Attribute-Efficient and Non-adaptive Learning of Parities and DNF Expressions∗

Journal of Machine Learning Research[removed]1460 Submitted 5/06; Revised 10/06; Published 7/07 Attribute-Efficient and Non-adaptive Learning of Parities and DNF Expressions∗

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Source URL: jmlr.org

Language: English - Date: 2007-07-10 13:02:43
40From: AAAI-90 Proceedings. Copyright ©1990, AAAI (www.aaai.org). All rights reserved.  Probably Approximately Correct Learning

From: AAAI-90 Proceedings. Copyright ©1990, AAAI (www.aaai.org). All rights reserved. Probably Approximately Correct Learning

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Source URL: aaaipress.org

Language: English - Date: 2006-01-09 20:07:23