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Learning Theory

5312 directly classified papers

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Papers

Safe Reinforcement Learning with Instantaneous Constraints: The Role of Aggressive Exploration AAAI 2024
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications JMLR 2024
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets JMLR 2024
Active Learning with Simple Questions COLT 2024
Topological obstruction to the training of shallow ReLU neural networks NIPS 2024
Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut NIPS 2024
Space-Time Continuous PDE Forecasting using Equivariant Neural Fields NIPS 2024
Globally Convergent Variational Inference NIPS 2024
What do Graph Neural Networks learn? Insights from Tropical Geometry NIPS 2024
Double-Descent Curves in Neural Networks: A New Perspective Using Gaussian Processes AAAI 2024
Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery AAAI 2024
LatEval: An Interactive LLMs Evaluation Benchmark with Incomplete Information from Lateral Thinking Puzzles COLING 2024
Towards Sharper Generalization Bounds for Adversarial Contrastive Learning IJCAI 2024
Hardness of Learning Neural Networks under the Manifold Hypothesis NIPS 2024
Provable Acceleration of Nesterov’s Accelerated Gradient Method over Heavy Ball Method in Training Over-Parameterized Neural Networks IJCAI 2024
Classification with Deep Neural Networks and Logistic Loss JMLR 2024
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation NIPS 2024
Collaborative Performance Prediction for Large Language Models EMNLP 2024
Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning NIPS 2024
Trajectory Data Suffices for Statistically Efficient Learning in Offline RL with Linear $q^\pi$-Realizability and Concentrability NIPS 2024
Regularization and Optimal Multiclass Learning COLT 2024
Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach AAAI 2024
Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning NIPS 2024
Runtime Analysis of the (μ + 1) GA: Provable Speed-Ups from Strong Drift towards Diverse Populations AAAI 2024
Achieving $\tilde{O}(1/\epsilon)$ Sample Complexity for Constrained Markov Decision Process NIPS 2024