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Learning Theory

5312 directly classified papers

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Papers

Lipschitz Bandits: Regret Lower Bound and Optimal Algorithms COLT 2014
Altitude Training: Strong Bounds for Single-Layer Dropout NIPS 2014
A New Perspective on Learning Linear Separators with Large L_qL_p Margins AISTATS 2014
Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees AISTATS 2014
A Finite-Sample Generalization Bound for Semiparametric Regression: Partially Linear Models AISTATS 2014
Selective Sampling with Drift AISTATS 2014
Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes? AISTATS 2014
PAC-Bayesian Theory for Transductive Learning AISTATS 2014
Sparse Polynomial Learning and Graph Sketching NIPS 2014
Matrix Completion with the Trace Norm: Learning, Bounding, and Transducing JMLR 2014
Learning to Optimize via Information-Directed Sampling NIPS 2014
Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures NIPS 2014
Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation NIPS 2014
Online Decision-Making in General Combinatorial Spaces NIPS 2014
Probably Approximately Correct MDP Learning and Control With Temporal Logic Constraints RSS 2014
Exploiting easy data in online optimization NIPS 2014
Rates of Convergence for Nearest Neighbor Classification NIPS 2014
From Stochastic Mixability to Fast Rates NIPS 2014
Sample Compression for Multi-label Concept Classes COLT 2014
An Inequality with Applications to Structured Sparsity and Multitask Dictionary Learning COLT 2014
Sample Complexity Bounds on Differentially Private Learning via Communication Complexity COLT 2014
Online Learning with Composite Loss Functions COLT 2014
Orbit Regularization NIPS 2014
Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors AISTATS 2014
Non-Asymptotic Analysis of Relational Learning with One Network AISTATS 2014