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Learning Theory

5,334 papers

Papers per year

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Papers

Batch Policy Learning under Constraints ICML 2019
Target-Based Temporal-Difference Learning ICML 2019
Online Learning to Rank with Features ICML 2019
Towards a Unified Analysis of Random Fourier Features ICML 2019
Cautious Regret Minimization: Online Optimization with Long-Term Budget Constraints ICML 2019
PA-GD: On the Convergence of Perturbed Alternating Gradient Descent to Second-Order Stationary Points for Structured Nonconvex Optimization ICML 2019
Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards ICML 2019
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models ICML 2019
Optimality Implies Kernel Sum Classifiers are Statistically Efficient ICML 2019
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models ICML 2019
Approximation and non-parametric estimation of ResNet-type convolutional neural networks ICML 2019
Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians ICML 2019
The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study ICML 2019
Towards Understanding Knowledge Distillation ICML 2019
Learning to Collaborate in Markov Decision Processes ICML 2019
On the Spectral Bias of Neural Networks ICML 2019
Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise ICML 2019
First-Order Adversarial Vulnerability of Neural Networks and Input Dimension ICML 2019
Concentration Inequalities for Conditional Value at Risk ICML 2019
Understanding Priors in Bayesian Neural Networks at the Unit Level ICML 2019
State-Regularized Recurrent Neural Networks ICML 2019
On the Generalization Gap in Reparameterizable Reinforcement Learning ICML 2019
CapsAndRuns: An Improved Method for Approximately Optimal Algorithm Configuration ICML 2019
Sample-Optimal Parametric Q-Learning Using Linearly Additive Features ICML 2019
Rademacher Complexity for Adversarially Robust Generalization ICML 2019