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Learning Theory

5312 directly classified papers

Papers per year

Papers

WL meet VC ICML 2023
On Batch Teaching Without Collusion JMLR 2023
Lower Bounds and Accelerated Algorithms for Bilevel Optimization JMLR 2023
Probing Graph Decomposition for Argument Pair Extraction ACL 2023
Are Sample-Efficient NLP Models More Robust? ACL 2023
Delving into the Openness of CLIP ACL 2023
Learning to Generate Equitable Text in Dialogue from Biased Training Data ACL 2023
Probing for Hyperbole in Pre-Trained Language Models ACL 2023
Rethinking Document-Level Relation Extraction: A Reality Check ACL 2023
Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization CVPR 2023
Make Every Example Count: On the Stability and Utility of Self-Influence for Learning from Noisy NLP Datasets EMNLP 2023
VO$Q$L: Towards Optimal Regret in Model-free RL with Nonlinear Function Approximation COLT 2023
Online Reinforcement Learning in Stochastic Continuous-Time Systems COLT 2023
Exponential Hardness of Reinforcement Learning with Linear Function Approximation COLT 2023
ReCode: Robustness Evaluation of Code Generation Models ACL 2023
On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring COLT 2023
On “Scientific Debt” in NLP: A Case for More Rigour in Language Model Pre-Training Research ACL 2023
Quantifying Train-Evaluation Overlap with Nearest Neighbors ACL 2023
Shortest Program Interpolation Learning COLT 2023
Sparsity-aware generalization theory for deep neural networks COLT 2023
SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics COLT 2023
Limits of Model Selection under Transfer Learning COLT 2023
Local Glivenko-Cantelli COLT 2023
Tighter PAC-Bayes Bounds Through Coin-Betting COLT 2023
Certifiable Out-of-Distribution Generalization AAAI 2023