| 2024 | Universal Rates for Regression: Separations between Cut-Off and Absolute Loss. | Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas |
| 2024 | The Best Arm Evades: Near-optimal Multi-pass Streaming Lower Bounds for Pure Exploration in Multi-armed Bandits. | Sepehr Assadi, Chen Wang |
| 2024 | Open Problem: Can Local Regularization Learn All Multiclass Problems? | Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng |
| 2024 | Regularization and Optimal Multiclass Learning. | Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng |
| 2024 | Universally Instance-Optimal Mechanisms for Private Statistical Estimation. | Hilal Asi, John C. Duchi, Saminul Haque, Zewei Li, Feng Ruan |
| 2024 | Mode Estimation with Partial Feedback. | Charles Arnal, Vivien Cabannes, Vianney Perchet |
| 2024 | Two fundamental limits for uncertainty quantification in predictive inference. | Felipe Areces, Chen Cheng, John C. Duchi, Kuditipudi Rohith |
| 2024 | Fast parallel sampling under isoperimetry. | Nima Anari, Sinho Chewi, Thuy-Duong Vuong |
| 2024 | Mitigating Covariate Shift in Misspecified Regression with Applications to Reinforcement Learning. | Philip Amortila, Tongyi Cao, Akshay Krishnamurthy |
| 2024 | A Unified Characterization of Private Learnability via Graph Theory. | Noga Alon, Shay Moran, Hilla Schefler, Amir Yehudayoff |
| 2024 | Metalearning with Very Few Samples Per Task. | Maryam Aliakbarpour, Konstantina Bairaktari, Gavin Brown, Adam Smith, Nathan Srebro, Jonathan R. Ullman |
| 2024 | Majority-of-Three: The Simplest Optimal Learner? | Ishaq Aden-Ali, Mikael Mller Handgsgaard, Kasper Green Larsen, Nikita Zhivotovskiy |
| 2024 | Limits of Approximating the Median Treatment Effect. | Raghavendra Addanki, Siddharth Bhandari |
| 2024 | Scale-free Adversarial Reinforcement Learning. | Mingyu Chen, Xuezhou Zhang |
| 2024 | Minimax-optimal reward-agnostic exploration in reinforcement learning. | Gen Li, Yuling Yan, Yuxin Chen, Jianqing Fan |
| 2024 | Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract. | Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith |
| 2024 | Efficient Algorithms for Learning Monophonic Halfspaces in Graphs. | Marco Bressan, Emmanuel Esposito, Maximilian Thiessen |
| 2024 | A Theory of Interpretable Approximations. | Marco Bressan, Nicol Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen |
| 2024 | Refined Sample Complexity for Markov Games with Independent Linear Function Approximation (Extended Abstract). | Yan Dai, Qiwen Cui, Simon S. Du |
| 2024 | On sampling diluted Spin-Glasses using Glauber Dynamics. | Charilaos Efthymiou, Kostas Zampetakis |
| 2024 | Learnability Gaps of Strategic Classification. | Lee Cohen, Yishay Mansour, Shay Moran, Han Shao |
| 2024 | On the sample complexity of parameter estimation in logistic regression with normal design. | Daniel Hsu, Arya Mazumdar |
| 2024 | Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing (Extended Abstract). | Yihan Zhang, Hong Chang Ji, Ramji Venkataramanan, Marco Mondelli |
| 2024 | Dual VC Dimension Obstructs Sample Compression by Embeddings. | Zachary Chase, Bogdan Chornomaz, Steve Hanneke, Shay Moran, Amir Yehudayoff |
| 2023 | A new ranking scheme for modern data and its application to two-sample hypothesis testing. | Doudou Zhou, Hao Chen |