← Optimization & Theory
Machine Learning › Optimization & Theory ›

Sample Complexity

97 directly classified papers

Papers per year

Papers

Revisiting Sample Size Determination in Natural Language Understanding ACL 2023
Promises and Pitfalls of Threshold-based Auto-labeling NIPS 2023
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits NIPS 2023
Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms NIPS 2023
On Gap-dependent Bounds for Offline Reinforcement Learning NIPS 2022
On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood NIPS 2022
Towards Bridging Sample Complexity and Model Capacity AAAI 2022
Estimation of Entropy in Constant Space with Improved Sample Complexity NIPS 2022
A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation NIPS 2022
Learning and Covering Sums of Independent Random Variables with Unbounded Support NIPS 2022
Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes NIPS 2022
Linear Label Ranking with Bounded Noise NIPS 2022
The Sample Complexity of One-Hidden-Layer Neural Networks NIPS 2022
The Sample Complexity of Level Set Approximation AISTATS 2021
The Sample Complexity of Teaching by Reinforcement on Q-Learning AAAI 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
On the Sample Complexity of Learning under Geometric Stability NIPS 2021
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations NIPS 2021
Tighter Expected Generalization Error Bounds via Wasserstein Distance NIPS 2021
Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model NIPS 2021
Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates NIPS 2021
Navigating to the Best Policy in Markov Decision Processes NIPS 2021
Identification of the Generalized Condorcet Winner in Multi-dueling Bandits NIPS 2021
A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning NIPS 2021