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Empirical risk minimization
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11	Alexander (Sasha) Rakhlin Department of Statistics, The Wharton School, University of Pennsylvania 465 Jon M. Huntsman Hall, Philadelphia, PAEmail: rakhlin at wharton.upenn.edu ACADEMIC APPOINTMENTS - Add to Reading List Source URL: www-stat.wharton.upenn.edu Language: English - Date: 2016-02-29 18:39:41 Machine learning Learning Cognition Neuroscience Cognitive science Computational neuroscience Stability Conference on Neural Information Processing Systems Empirical risk minimization Learning theory Statistical learning theory Game theory
12	Norm-regularized empirical risk minimization Sara van de Geer ETH Z¨ urich The usefulness of `1 -norm regularization in high-dimensional problems is nowadays well recognized. A fundamental property of the `1 -norm that Add to Reading List Source URL: papersjds15.sfds.asso.fr Language: English - Date: 2015-05-05 11:56:51
13	Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour Google Research and Tel Aviv Univ. Add to Reading List Source URL: www.cs.nyu.edu Language: English - Date: 2009-11-02 10:14:29 Machine learning Information theory Operator theory Kullback–Leibler divergence Thermodynamics Empirical risk minimization Entropy Hilbert space Multivariate normal distribution Statistics Statistical theory Probability and statistics
14	New Analysis and Algorithm for Learning with Drifting Distributions Mehryar Mohri1,2 and Andres Mu˜noz Medina1 arXiv:1205.4343v1 [cs.LG] 19 May 2012 Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-02-01 14:59:47 Machine learning Empirical risk minimization
15	Learning Submodular Losses with the Lov´ asz Hinge Jiaqian Yu, Matthew Blaschko To cite this version: Jiaqian Yu, Matthew Blaschko. Learning Submodular Losses with the Lov´asz Hinge. International Conference on Machine Add to Reading List Source URL: hal.inria.fr Language: English Machine learning Submodular set function Order theory Convex analysis Supermodular function Hinge loss Empirical risk minimization Linear programming Vector space Mathematics Mathematical optimization Algebra
16	Comparing performance and robustness of SVM and ANN for fault diagnosis in a centrifugal pump Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-15 22:31:53 Learning Statistical classification Support vector machines Stability Empirical risk minimization Perceptron Artificial neural network Least squares support vector machine Machine learning Statistics Neural networks
17	On-line learning Where are we so far? Antoine Cornuéjols MMIP, AgroParisTech, Paris October 9th, 2008 Add to Reading List Source URL: www.lri.fr Language: English - Date: 2008-10-17 03:37:57 Mathematical optimization Variance Statistics Machine learning Empirical risk minimization
18	Topics in Structured Prediction: Problems and Approaches DRAFT Ankan Saha June 9, 2010 Add to Reading List Source URL: people.cs.uchicago.edu Language: English - Date: 2010-06-09 21:19:59 Supervised learning Structured prediction Structured learning Support vector machine Empirical risk minimization Regression analysis Natural language processing Algorithm Pattern recognition Statistics Machine learning Artificial intelligence
19	On-line learning Where are we so far? Antoine Cornuéjols MMIP, AgroParisTech, Paris Int. workshop on Data Stream Management and Mining Add to Reading List Source URL: www.lri.fr Language: English - Date: 2008-11-05 12:48:40 Machine learning Support vector machine Mathematical optimization Perceptron Learning Artificial intelligence Statistics Neural networks Empirical risk minimization
20	JMLR: Workshop and Conference Proceedings vol–32 24th Annual Conference on Learning Theory Sample Complexity Bounds for Differentially Private Learning Add to Reading List Source URL: cseweb.ucsd.edu Language: English - Date: 2011-09-27 03:12:47 Ethics Artificial intelligence Learning Statistical classification Applied probability Exponential mechanism Differential privacy Empirical risk minimization VC dimension Machine learning Data privacy Statistics