| 2025 | Regret Bounds for Robust Online Decision Making. | Alexander Appel, Vanessa Kosoy |
| 2025 | Better Private Distribution Testing by Leveraging Unverified Auxiliary Data. | Maryam Aliakbarpour, Arnav Burudgunte, Clment L. Canonne, Ronitt Rubinfeld |
| 2025 | Computable learning of natural hypothesis classes. | Syed Akbari, Matthew Harrison-Trainor |
| 2025 | Optimistic Q-learning for average reward and episodic reinforcement learning extended abstract. | Priyank Agrawal, Shipra Agrawal |
| 2024 | Gap-Free Clustering: Sensitivity and Robustness of SDP. | Matthew Zurek, Yudong Chen |
| 2024 | Optimal Multi-Distribution Learning. | Zihan Zhang, Wenhao Zhan, Yuxin Chen, Simon S. Du, Jason D. Lee |
| 2024 | Settling the sample complexity of online reinforcement learning. | Zihan Zhang, Yuxin Chen, Jason D. Lee, Simon S. Du |
| 2024 | Fast two-time-scale stochastic gradient method with applications in reinforcement learning. | Sihan Zeng, Thinh T. Doan |
| 2024 | Counting Stars is Constant-Degree Optimal For Detecting Any Planted Subgraph: Extended Abstract. | Xifan Yu, Ilias Zadik, Peiyuan Zhang |
| 2024 | Multiple-output composite quantile regression through an optimal transport lens. | Xuzhi Yang, Tengyao Wang |
| 2024 | Top-K ranking with a monotone adversary. | Yuepeng Yang, Antares Chen, Lorenzo Orecchia, Cong Ma |
| 2024 | Bridging the Gap: Rademacher Complexity in Robust and Standard Generalization. | Jiancong Xiao, Ruoyu Sun, Qi Long, Weijie Su |
| 2024 | Preface. | |
| 2024 | Oracle-Efficient Hybrid Online Learning with Unknown Distribution. | Changlong Wu, Jin Sima, Wojciech Szpankowski |
| 2024 | Large Stepsize Gradient Descent for Logistic Loss: Non-Monotonicity of the Loss Improves Optimization Efficiency. | Jingfeng Wu, Peter L. Bartlett, Matus Telgarsky, Bin Yu |
| 2024 | Optimal score estimation via empirical Bayes smoothing. | Andre Wibisono, Yihong Wu, Kaylee Yingxi Yang |
| 2024 | Nearly Optimal Regret for Decentralized Online Convex Optimization. | Yuanyu Wan, Tong Wei, Mingli Song, Lijun Zhang |
| 2024 | Nonlinear spiked covariance matrices and signal propagation in deep neural networks. | Zhichao Wang, Denny Wu, Zhou Fan |
| 2024 | Open problem: Convergence of single-timescale mean-field Langevin descent-ascent for two-player zero-sum games. | Guillaume Wang, Lnac Chizat |
| 2024 | Efficient Algorithms for Attributed Graph Alignment with Vanishing Edge Correlation Extended Abstract. | Ziao Wang, Weina Wang, Lele Wang |
| 2024 | Pruning is Optimal for Learning Sparse Features in High-Dimensions. | Nuri Mert Vural, Murat A. Erdogdu |
| 2024 | Fast, blind, and accurate: Tuning-free sparse regression with global linear convergence. | Claudio Mayrink Verdun, Oleh Melnyk, Felix Krahmer, Peter Jung |
| 2024 | Active Learning with Simple Questions. | Vasilis Kontonis, Mingchen Ma, Christos Tzamos |
| 2024 | Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning. | Sattar Vakili |
| 2024 | Improved Hardness Results for Learning Intersections of Halfspaces. | Stefan Tiegel |