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Learning Theory

6,809 papers

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Papers

Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels ICML 2021 Query Complexity of Adversarial Attacks ICML 2021 Randomized Exploration in Reinforcement Learning with General Value Function Approximation ICML 2021 RATT: Leveraging Unlabeled Data to Guarantee Generalization ICML 2021 Reanalyzing the Most Probable Sentence Problem: A Case Study in Explicating the Role of Entropy in Algorithmic Complexity EACL 2021 Reconstructing weighted voting schemes from partial information about their power indices COLT 2021 Recursive prosody is not finite-state ACL 2021 Refined approachability algorithms and application to regret minimization with global costs JMLR 2021 Refined Learning Bounds for Kernel and Approximate k-Means NeurIPS 2021 Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints ICML 2021 Regret Bounds for Batched Bandits AAAI 2021 Regret Minimization in Heavy-Tailed Bandits COLT 2021 Regulating Greed Over Time in Multi-Armed Bandits JMLR 2021 Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection NeurIPS 2021 Reinforcement Learning in Parametric MDPs with Exponential Families AISTATS 2021 Reinforcement Learning in Reward-Mixing MDPs NeurIPS 2021 Relative Deviation Margin Bounds ICML 2021 Relative stability toward diffeomorphisms indicates performance in deep nets NeurIPS 2021 Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization NeurIPS 2021 Rethink the Connections among Generalization, Memorization, and the Spectral Bias of DNNs IJCAI 2021 Revealing the Structure of Deep Neural Networks via Convex Duality ICML 2021 Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning JMLR 2021 Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits AAAI 2021 Reward Biased Maximum Likelihood Estimation for Reinforcement Learning L4DC 2021 Ridge Regression with Over-parametrized Two-Layer Networks Converge to Ridgelet Spectrum AISTATS 2021