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Computational learning theory
Results: 425

#	Item
291	Efficient discriminative learning of Bayesian network classifier via Boosted Augmented Naive Bayes Yushi Jing College of Computing, Georgia Institute of Technology, Atlanta, GA[removed]USA Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:15:42 Statistical classification Statistical models Naive Bayes classifier Ensemble learning Bayesian inference Bayesian network Computational learning theory Averaged one-dependence estimators AdaBoost Statistics Bayesian statistics Machine learning
292	The True Sample Complexity of Active Learning⋆ Maria-Florina Balcan1 , Steve Hanneke2 , and Jennifer Wortman Vaughan3⋆⋆ 1 3 Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2010-02-27 23:58:39 Theoretical computer science Statistics Mathematics Learning Statistical classification VC dimension Algorithm Machine learning Computational learning theory Applied mathematics
293	Learning Submodular Functions⋆ Maria-Florina Balcan1 and Nicholas J. A. Harvey2 1 Georgia Institute of Technology, School of Computer Science. 2 Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2012-07-04 16:58:41 Submodular set function Operations research Machine learning Matroid Mathematical optimization Computational learning theory Algorithm Mathematics Theoretical computer science Applied mathematics
294	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 Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2009-09-02 22:40:44 Learning Transduction Semi-supervised learning Supervised learning Pattern recognition Co-training Probably approximately correct learning Word-sense disambiguation Computational learning theory Machine learning Statistics Artificial intelligence
295	JMLR: Workshop and Conference Proceedings vol[removed]–24 Learning Valuation Functions Maria Florina Balcan NINAMF @ CC . GATECH . EDU Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2012-05-24 21:07:27 Computational complexity theory Analysis of algorithms Field theory Fourier analysis Submodular set function Subadditivity Valuation Approximation algorithm Big O notation Mathematics Theoretical computer science Mathematical analysis
296	MARIA-FLORINA BALCAN Carnegie Mellon University Pittsburgh, PA 15213 − 3891 [removed] www.cs.cmu.edu/~ninamf/ Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2014-08-16 22:01:21 Avrim Blum International Conference on Machine Learning Computational learning theory Conference on Neural Information Processing Systems Semi-supervised learning Balcan Co-training Carnegie Mellon School of Computer Science Theoretical computer science Machine learning Artificial intelligence Learning
297	JMLR: Workshop and Conference Proceedings vol[removed]–22 Distributed Learning, Communication Complexity and Privacy Maria-Florina Balcan∗ Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2012-06-04 16:01:05 Computational learning theory Statistical classification Machine learning Computational complexity theory Probably approximately correct learning Communication complexity Margin classifier Supervised learning VC dimension Theoretical computer science Statistics Applied mathematics
298	Review of Le ture 6 • The VC Inequality • mH(N ) is polynomial Add to Reading List Source URL: www.amlbook.com Language: English VC dimension Differentiation rules Mathematics Mathematical sciences Mechanical engineering Applied mathematics Computational learning theory Dimension Statistical classification
299	JMLR: Workshop and Conference Proceedings vol[removed]–34 Robust Interactive Learning Maria Florina Balcan NINAMF @ CC . GATECH . EDU Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2012-05-24 20:13:01 Applied mathematics Computational complexity theory Learning Empirical risk minimization Probably approximately correct learning Decision tree model Active learning Machine learning Theoretical computer science Artificial intelligence
300	The Power of Localization for Efficiently Learning Linear Separators with Noise Pranjal Awasthi [removed] Maria Florina Balcan Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2014-02-04 22:35:39 Statistics Artificial intelligence Statistical classification Learning Supervised learning Information theory Linear classifier Computational learning theory PP Machine learning Applied mathematics Cybernetics

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