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Learning Theory

5312 directly classified papers

Papers per year

Papers

Online Learning: Beyond Regret COLT 2011
Multiclass Learnability and the ERM principle COLT 2011
Distribution-Independent Evolvability of Linear Threshold Functions COLT 2011
Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas COLT 2011
A Close Look to Margin Complexity and Related Parameters COLT 2011
Agnostic KWIK learning and efficient approximate reinforcement learning COLT 2011
Bounds on Individual Risk for Log-loss Predictors COLT 2011
Missing Information Impediments to Learnability COLT 2011
Discussion of “Contextual Bandit Algorithms with Supervised Learning Guarantees” AISTATS 2011
A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences COLT 2011
Sparsity Regret Bounds for Individual Sequences in Online Linear Regression COLT 2011
Weisfeiler-Lehman Graph Kernels JMLR 2011
Contextual Bandit Algorithms with Supervised Learning Guarantees AISTATS 2011
Improved Loss Bounds For Multiple Kernel Learning AISTATS 2011
Generalization Bound for Infinitely Divisible Empirical Process AISTATS 2011
Action-Gap Phenomenon in Reinforcement Learning NIPS 2011
Lower Bounds for Passive and Active Learning NIPS 2011
k-NN Regression Adapts to Local Intrinsic Dimension NIPS 2011
Prediction strategies without loss NIPS 2011
Active Learning with a Drifting Distribution NIPS 2011
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers NIPS 2011
Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss NIPS 2011
Autonomous Learning of Action Models for Planning NIPS 2011
Agnostic Selective Classification NIPS 2011
Optimal learning rates for least squares SVMs using Gaussian kernels NIPS 2011