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Learning Theory

5,312 papers

Papers per year

Papers

On Gap-dependent Bounds for Offline Reinforcement Learning NIPS 2022
Near-Optimal Multi-Agent Learning for Safe Coverage Control NIPS 2022
Independence Testing for Bounded Degree Bayesian Networks NIPS 2022
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity NIPS 2022
Stability Analysis and Generalization Bounds of Adversarial Training NIPS 2022
Linear Label Ranking with Bounded Noise NIPS 2022
Task Discovery: Finding the Tasks that Neural Networks Generalize on NIPS 2022
On Batch Teaching with Sample Complexity Bounded by VCD NIPS 2022
Sequential Information Design: Learning to Persuade in the Dark NIPS 2022
On the Importance of Gradient Norm in PAC-Bayesian Bounds NIPS 2022
On global convergence of ResNets: From finite to infinite width using linear parameterization NIPS 2022
On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory NIPS 2022
On the non-universality of deep learning: quantifying the cost of symmetry NIPS 2022
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference NIPS 2022
When Combinatorial Thompson Sampling meets Approximation Regret NIPS 2022
Tikhonov Regularization is Optimal Transport Robust under Martingale Constraints NIPS 2022
Optimal Binary Classification Beyond Accuracy NIPS 2022
On Learning and Refutation in Noninteractive Local Differential Privacy NIPS 2022
Modeling the Machine Learning Multiverse NIPS 2022
Measures of Information Reflect Memorization Patterns NIPS 2022
Fine-Grained Analysis of Stability and Generalization for Modern Meta Learning Algorithms NIPS 2022
Most Activation Functions Can Win the Lottery Without Excessive Depth NIPS 2022
Dynamic Pricing with Monotonicity Constraint under Unknown Parametric Demand Model NIPS 2022
Benign Underfitting of Stochastic Gradient Descent NIPS 2022
Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning NIPS 2022