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Statistical learning theory
Results: 800

#	Item
621	Discriminative Learning for Differing Training and Test Distributions Steffen Bickel Michael Br¨ uckner Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:25:37 Econometrics Estimation theory Maximum likelihood Linear classifier Loss function Support vector machine Normal distribution Spectral theory of ordinary differential equations Statistics Statistical theory Statistical classification
622	Exploration and Apprenticeship Learning in Reinforcement Learning Pieter Abbeel Andrew Y. Ng Computer Science Department, Stanford University Stanford, CA 94305, USA Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:16:12 Estimation theory Statistical theory Dynamic programming Markov decision process Reinforcement learning Markov chain Maximum likelihood XTR Statistics Markov processes Markov models
623	Learning from Noisy Side Information by Generalized Maximum Entropy Model Add to Reading List Source URL: www.icml2010.org Language: English - Date: 2010-06-13 09:06:35 Statistical theory Machine learning Multivariate statistics Information Age Mutual information Principle of maximum entropy Cluster analysis Entropy Hierarchical clustering Statistics Probability and statistics Information theory
624	Sparse Probabilistic Classifiers Romain H´ erault [removed] HEUDIASYC, Universit´e de Technologie de Compi`egne, BP 20529, 60205 Compi`egne cedex, France Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:24:01 Statistical theory Regression analysis Econometrics Logistic regression Linear classifier Logistic function Support vector machine Pattern recognition Linear discriminant analysis Statistics Statistical classification Machine learning
625	Listwise Approach to Learning to Rank - Theory and Algorithm Fen Xia* Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, P. R. China. [removed] Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-05-21 03:01:42 Machine learning M-estimators Information retrieval Learning to rank Statistical theory Stochastic optimization Function Loss function Normal distribution Mathematics Statistics Mathematical analysis
626	Statistical Learning of Arbitrary Computable Classifiers David Soloveichik California Institute of Technology Department of Computation and Neural Systems MC[removed]Pasadena, CA 91125 Add to Reading List Source URL: www.dna.caltech.edu Language: English - Date: 2009-05-26 19:56:02 Computational learning theory Computability theory Theory of computation Machine learning Probably approximately correct learning Blum axioms Computable function Uniform convergence VC dimension Theoretical computer science Mathematics Applied mathematics
627	Problem Sets • Problem Set 3 – Distributed Tuesday, 3/18. – Due Thursday, 4/3 • Problem Set 4 Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2003-03-13 18:22:00 Machine learning Regression analysis Estimation theory Expectation–maximization algorithm Mixture model Segmentation Variance Parameter Statistics Data analysis Statistical models
628	Asymptotic Analysis of Generative Semi-Supervised Learning Joshua V. Dillon [removed] Krishnakumar Balasubramanian [removed] Add to Reading List Source URL: www.icml2010.org Language: English - Date: 2010-06-13 09:06:35 Statistical theory Supervised learning Semi-supervised learning Pattern recognition Maximum likelihood Bias of an estimator Fisher information Variance Statistics Machine learning Estimation theory
629	Local Similarity Discriminant Analysis Luca Cazzanti Applied Physics Lab, University of Washington, Seattle WA[removed]removed] Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:25:23 Multivariate statistics Bayesian statistics Statistical theory Linear discriminant analysis Naive Bayes classifier Support vector machine Shape context Classification rule Pattern recognition Statistics Statistical classification Machine learning
630	Laplace Maximum Margin Markov Networks Jun Zhu†∗ [removed] Eric P. Xing† [removed] Bo Zhang∗ Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-05-21 03:17:20 Machine learning Graphical models Conditional random field Theoretical computer science Kullback–Leibler divergence Pattern recognition Gibbs sampling Support vector machine Principle of maximum entropy Statistics Statistical theory Bayesian statistics

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