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Statistical learning theory
Results: 800

#	Item
711	Map-Reduce for Machine Learning on Multicore Cheng-Tao Chu ∗ [removed] Sang Kyun Kim ∗ [removed] Add to Reading List Source URL: www.cs.stanford.edu Language: English - Date: 2007-04-03 19:22:00 Multivariate statistics Learning Statistical classification Expectation–maximization algorithm Support vector machine Principal component analysis Machine learning Algorithm Time complexity Statistics Regression analysis Estimation theory
712	Journal of Artificial Intelligence Research[removed]Submitted 05/04; published[removed]Finding Approximate POMDP Solutions Through Belief Compression Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2005-01-30 19:00:16 Stochastic control Multivariate statistics Partially observable Markov decision process Statistical theory Automated planning and scheduling Principal component analysis Reinforcement learning Dimension reduction Markov decision process Statistics Dynamic programming Markov processes
713	Closed-Form Supervised Dimensionality Reduction with Generalized Linear Models Irina Rish IBM T.J. Watson Research Center, Yorktown Heights, NY[removed]USA Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2009-08-10 09:51:56 Statistical classification Regression analysis Statistical theory Supervised learning Support vector machine Dimension reduction Loss function Non-negative matrix factorization Principal component analysis Statistics Machine learning Multivariate statistics
714	The Power of Localization for Efficiently Learning Linear Separators with Noise Pranjal Awasthi [removed] Maria Florina Balcan Add to Reading List Source URL: www.phillong.info Language: English - Date: 2014-03-07 12:21:42 Learning Machine learning Statistical classification Supervised learning Information theory Vector space Stability Linear classifier PP Algebra Mathematics Cybernetics
715	The Support Vector Decomposition Machine Francisco Pereira1,3 [removed] Geoffrey Gordon2 [removed] Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2006-05-03 09:58:16 Machine learning Statistical classification Linear algebra Matrix theory Support vector machine Singular value decomposition Dimension reduction Independent component analysis Statistics Algebra Multivariate statistics
716	Using the Doubling Dimension to Analyze the Generalization of Learning Algorithms Nader H. Bshouty∗ Technion Yi Li Add to Reading List Source URL: www.phillong.info Language: English - Date: 2013-08-07 11:59:37 Statistical classification Generalized functions Mathematics Dimension VC dimension Distribution Probably approximately correct learning Computational learning theory Mathematical analysis Statistics
717	A Spectral Learning Approach to Knowledge Tracing Mohammad H. Falakmasir Zachary A. Pardos Intelligent Systems Program, Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2013-05-19 11:47:35 Estimation theory Expectation–maximization algorithm Missing data Hidden Markov model Root-mean-square deviation Mathematical model Regression analysis Grid search Statistics Machine learning Statistical inference
718	A Bayesian Matrix Model for Relational Data Geoffrey J. Gordon Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213, USA Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2009-12-01 11:19:09 Statistical theory Markov chain Monte Carlo Multivariate statistics Conjugate prior Metropolis–Hastings algorithm Maximum likelihood Bayesian inference Generalized linear model Gibbs sampling Statistics Bayesian statistics Estimation theory
719	A Scalable Distributed Algorithm for Shape Transformation in Multi-Robot Systems Ramprasad Ravichandran1 , Geoffrey Gordon2 , Seth Copen Goldstein3 Institute, 2 Machine Learning Department, 3 Computer Science Department Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2007-08-15 14:34:54 Stability Algorithm Lyapunov stability Mathematics Applied mathematics Logic Estimation theory Estimator Statistical inference
720	Noname manuscript No. (will be inserted by the editor) Linear classifiers are nearly optimal when hidden variables have diverse effects Add to Reading List Source URL: www.phillong.info Language: English - Date: 2013-08-07 11:59:18 Statistical classification Machine learning Conditional independence Independence Linear classifier Variance Statistics Probability theory Statistical dependence

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