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Learning Theory

5,312 papers

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Papers

Dynamic Balancing for Model Selection in Bandits and RL ICML 2021
Adversarial Robustness Guarantees for Random Deep Neural Networks ICML 2021
Toward Better Generalization Bounds with Locally Elastic Stability ICML 2021
On the Inherent Regularization Effects of Noise Injection During Training ICML 2021
How rotational invariance of common kernels prevents generalization in high dimensions ICML 2021
Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning ICML 2021
Provably Strict Generalisation Benefit for Equivariant Models ICML 2021
Implicit Bias of Linear RNNs ICML 2021
Revealing the Structure of Deep Neural Networks via Convex Duality ICML 2021
Learning Bounds for Open-Set Learning ICML 2021
Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach ICML 2021
Provably Correct Optimization and Exploration with Non-linear Policies ICML 2021
Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins ICML 2021
Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise ICML 2021
Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning ICML 2021
RATT: Leveraging Unlabeled Data to Guarantee Generalization ICML 2021
Let’s Agree to Degree: Comparing Graph Convolutional Networks in the Message-Passing Framework ICML 2021
Query Complexity of Adversarial Attacks ICML 2021
The Heavy-Tail Phenomenon in SGD ICML 2021
Adapting to Delays and Data in Adversarial Multi-Armed Bandits ICML 2021
Model Performance Scaling with Multiple Data Sources ICML 2021
Logarithmic Regret for Reinforcement Learning with Linear Function Approximation ICML 2021
Zeroth-Order Non-Convex Learning via Hierarchical Dual Averaging ICML 2021
Learning Curves for Analysis of Deep Networks ICML 2021
On the Random Conjugate Kernel and Neural Tangent Kernel ICML 2021