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sample complexity

1158 papers

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reinforcement learning (4122) pac learning (280) multi-armed bandit (1091) markov decision process (788) learning theory (518) differential privacy (1010) stochastic optimization (1060) neural network (6616) active learning (1295) regret bound (1918)

Papers

Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition NIPS 2021
Multi-Armed Bandits with Bounded Arm-Memory: Near-Optimal Guarantees for Best-Arm Identification and Regret Minimization NIPS 2021
The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers NIPS 2021
Never Go Full Batch (in Stochastic Convex Optimization) NIPS 2021
Identification of the Generalized Condorcet Winner in Multi-dueling Bandits NIPS 2021
Towards Sample-efficient Overparameterized Meta-learning NIPS 2021
On the Sample Complexity of Privately Learning Axis-Aligned Rectangles NIPS 2021
A Regression Approach to Learning-Augmented Online Algorithms NIPS 2021
Predicting What You Already Know Helps: Provable Self-Supervised Learning NIPS 2021
Pure Exploration in Kernel and Neural Bandits NIPS 2021
A Theoretical Analysis of Fine-tuning with Linear Teachers NIPS 2021
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors NIPS 2021
A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning NIPS 2021
Towards Instance-Optimal Offline Reinforcement Learning with Pessimism NIPS 2021
Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees NIPS 2021
A Provably Efficient Sample Collection Strategy for Reinforcement Learning NIPS 2021
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction NIPS 2021
An Exponential Lower Bound for Linearly Realizable MDP with Constant Suboptimality Gap NIPS 2021
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings NIPS 2021
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms NIPS 2021
What Matters for Adversarial Imitation Learning? NIPS 2021
Uncertain Decisions Facilitate Better Preference Learning NIPS 2021
Nearly Horizon-Free Offline Reinforcement Learning NIPS 2021
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning NIPS 2021
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations NIPS 2021