Journal of Machine Learning Research1109 Submitted 6/10; Revised 2/11; Published 3/11 Differentially Private Empirical Risk Minimization Kamalika Chaudhuri

Source URL: www.jmlr.org

Neural networks Training neural networks - empirical risk minimization Feedforward neu 2

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Differentially Private Empirical Risk Minimization Kamalika Chaudhuri∗, Claire Monteleoni†, Anand D. Sarwate‡ June 1, 2010 Abstract Privacy-preserving machine learning algorithms are crucial for the increasingly co

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IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 53, NO. 11, NOVEMBERNonparametric Decentralized Detection Using Kernel Methods

Source URL: dept.stat.lsa.umich.edu

• Machine learning
• Learning
• Artificial intelligence
• Statistics
• Support vector machine
• Kernel method
• Statistical classification
• Positive-definite kernel
• Empirical risk minimization
• Loss function
• Statistical learning theory
• Bayes estimator

Empirical Risk Minimization for Support Vector Classiers Fernando P erez-Cruz, Member, IEEE, Angel Navia-V azquez, Member, IEEE, An bal R. Figueiras-Vidal, Senior Member, IEEE,

Source URL: www.tsc.uc3m.es

Local Rademacher Averages and Empirical Minimization Peter Bartlett Division of Computer Science and Department of Statistics UC Berkeley Joint work with

Source URL: www.stat.berkeley.edu

• Machine learning
• Empirical risk minimization
• Loss function

Journal of Machine Learning Research2583 Submitted 8/05; Revised 9/06; PublishedStability Properties of Empirical Risk Minimization over Donsker Classes

Source URL: jmlr.csail.mit.edu

Introduction to Statistical Learning Theory Olivier Bousquet1 , St´ephane Boucheron2 , and G´abor Lugosi3 1 Max-Planck Institute for Biological Cybernetics Spemannstr. 38, DT¨

Source URL: www.econ.upf.edu

• Machine learning
• Learning
• Artificial intelligence
• Supervised learning
• Statistical learning theory
• Empirical risk minimization
• Probability distribution
• Pattern recognition
• Generalization error
• Stability

Perturbation based Large Margin Approach for Ranking Eunho Yang University of Texas at Austin Ambuj Tewari

Source URL: dept.stat.lsa.umich.edu

• Machine learning
• Learning
• Artificial intelligence
• Support vector machines
• Learning to rank
• Hinge loss
• Ranking SVM
• Structured support vector machine
• Empirical risk minimization
• Mathematical optimization
• Supervised learning
• Distribution

Fast Rates for Exp-concave Empirical Risk Minimization Kfir Y. Levy Technion Haifa 32000, Israel

Source URL: tx.technion.ac.il