| 2025 | Generalization bounds for mixing processes via delayed online-to-PAC conversions. | Baptiste Abls, Eugenio Clerico, Gergely Neu |
| 2025 | When and why randomised exploration works (in linear bandits). | Marc Abeille, David Janz, Ciara Pike-Burke |
| 2024 | Corruption-Robust Lipschitz Contextual Search. | Shiliang Zuo |
| 2024 | Improving Adaptive Online Learning Using Refined Discretization. | Zhiyu Zhang, Heng Yang, Ashok Cutkosky, Ioannis Ch. Paschalidis |
| 2024 | Preface. | |
| 2024 | Adaptive Combinatorial Maximization: Beyond Approximate Greedy Policies. | Shlomi Weitzman, Sivan Sabato |
| 2024 | Alternating minimization for generalized rank one matrix sensing: Sharp predictions from a random initialization. | Kabir Aladin Verchand, Mengqi Lou, Ashwin Pananjady |
| 2024 | Universal Representation of Permutation-Invariant Functions on Vectors and Tensors. | Puoya Tabaghi, Yusu Wang |
| 2024 | Online Infinite-Dimensional Regression: Learning Linear Operators. | Unique Subedi, Vinod Raman, Ambuj Tewari |
| 2024 | Tight bounds for maximum ℓ | Stefan Stojanovic, Konstantin Donhauser, Fanny Yang |
| 2024 | A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions. | Vikrant Singhal |
| 2024 | Optimal Regret Bounds for Collaborative Learning in Bandits. | Amitis Shidani, Sattar Vakili |
| 2024 | Multiclass Online Learnability under Bandit Feedback. | Ananth Raman, Vinod Raman, Unique Subedi, Idan Mehalel, Ambuj Tewari |
| 2024 | The complexity of non-stationary reinforcement learning. | Binghui Peng, Christos H. Papadimitriou |
| 2024 | Adversarial Online Collaborative Filtering. | Stephen Pasteris, Fabio Vitale, Mark Herbster, Claudio Gentile, Andr Panisson |
| 2024 | Multiclass Learnability Does Not Imply Sample Compression. | Chirag Pabbaraju |
| 2024 | Adversarial Contextual Bandits Go Kernelized. | Gergely Neu, Julia Olkhovskaya, Sattar Vakili |
| 2024 | Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. | Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristbal Guzmn |
| 2024 | Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2024 | On the Computational Benefit of Multimodal Learning. | Zhou Lu |
| 2024 | Provable Accelerated Convergence of Nesterov's Momentum for Deep ReLU Neural Networks. | Fangshuo Liao, Anastasios Kyrillidis |
| 2024 | Slowly Changing Adversarial Bandit Algorithms are Efficient for Discounted MDPs. | Ian A. Kash, Lev Reyzin, Zishun Yu |
| 2024 | Agnostic Membership Query Learning with Nontrivial Savings: New Results and Techniques. | Ari Karchmer |
| 2024 | The Impossibility of Parallelizing Boosting. | Amin Karbasi, Kasper Green Larsen |
| 2024 | Efficient Agnostic Learning with Average Smoothness. | Steve Hanneke, Aryeh Kontorovich, Guy Kornowski |