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Learning Theory

5312 directly classified papers

Papers per year

Papers

Universal Kernels on Non-Standard Input Spaces NIPS 2010
Worst-Case Linear Discriminant Analysis NIPS 2010
Learning Bounds for Importance Weighting NIPS 2010
Smoothness, Low Noise and Fast Rates NIPS 2010
Permutation Complexity Bound on Out-Sample Error NIPS 2010
Sample Complexity of Testing the Manifold Hypothesis NIPS 2010
Multivariate Dyadic Regression Trees for Sparse Learning Problems NIPS 2010
Tight Sample Complexity of Large-Margin Learning NIPS 2010
Optimal learning rates for Kernel Conjugate Gradient regression NIPS 2010
Universal Consistency of Multi-Class Support Vector Classification NIPS 2010
Evidence-Specific Structures for Rich Tractable CRFs NIPS 2010
A Theory of Multiclass Boosting NIPS 2010
Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework NIPS 2010
Online Markov Decision Processes under Bandit Feedback NIPS 2010
Spike timing-dependent plasticity as dynamic filter NIPS 2010
Rates of convergence for the cluster tree NIPS 2010
On the Theory of Learnining with Privileged Information NIPS 2010
Two-Layer Generalization Analysis for Ranking Using Rademacher Average NIPS 2010
Empirical Bernstein Inequalities for U-Statistics NIPS 2010
Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data NIPS 2009
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness NIPS 2009
Kernels and learning curves for Gaussian process regression on random graphs NIPS 2009
Sufficient Conditions for Agnostic Active Learnable NIPS 2009
Discrete MDL Predicts in Total Variation NIPS 2009
Local Rules for Global MAP: When Do They Work ? NIPS 2009