| 2025 | Quantile Multi-Armed Bandits with 1-bit Feedback. | Ivan Lau, Jonathan Scarlett |
| 2025 | Sharp bounds on aggregate expert error. | Aryeh Kontorovich, Ariel Avital |
| 2025 | Information-Theoretic Guarantees for Recovering Low-Rank Tensors from Symmetric Rank-One Measurements. | Eren C. Kizildag |
| 2025 | Optimal and learned algorithms for the online list update problem with Zipfian accesses. | Piotr Indyk, Isabelle Quaye, Ronitt Rubinfeld, Sandeep Silwal |
| 2025 | Do PAC-Learners Learn the Marginal Distribution? | Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan |
| 2025 | A Complete Characterization of Learnability for Stochastic Noisy Bandits. | Steve Hanneke, Kun Wang |
| 2025 | For Universal Multiclass Online Learning, Bandit Feedback and Full Supervision are Equivalent. | Steve Hanneke, Amirreza Shaeiri, Hongao Wang |
| 2025 | Reliable Active Apprenticeship Learning. | Steve Hanneke, Liu Yang, Gongju Wang, Yulun Song |
| 2025 | A PAC-Bayesian Link Between Generalisation and Flat Minima. | Maxime Haddouche, Paul Viallard, Umut Simsekli, Benjamin Guedj |
| 2025 | Full Swap Regret and Discretized Calibration. | Maxwell Fishelson, Robert Kleinberg, Princewill Okoroafor, Renato Paes Leme, Jon Schneider, Yifeng Teng |
| 2025 | Is Transductive Learning Equivalent to PAC Learning? | Shaddin Dughmi, Yusuf Hakan Kalayci, Grayson York |
| 2025 | Boosting, Voting Classifiers and Randomized Sample Compression Schemes. | Arthur da Cunha, Kasper Green Larsen, Martin Ritzert |
| 2025 | Generalisation under gradient descent via deterministic PAC-Bayes. | Eugenio Clerico, Tyler Farghly, George Deligiannidis, Benjamin Guedj, Arnaud Doucet |
| 2025 | Near-Optimal Rates for O(1)-Smooth DP-SCO with a Single Epoch and Large Batches. | Christopher A. Choquette-Choo, Arun Ganesh, Abhradeep Guha Thakurta |
| 2025 | Differentially Private Multi-Sampling from Distributions. | Albert Cheu, Debanuj Nayak |
| 2025 | A Model for Combinatorial Dictionary Learning and Inference. | Avrim Blum, Kavya Ravichandran |
| 2025 | Nearly-tight Approximation Guarantees for the Improving Multi-Armed Bandits Problem. | Avrim Blum, Kavya Ravichandran |
| 2025 | Non-stochastic Bandits With Evolving Observations. | Yogev Bar-On, Yishay Mansour |
| 2025 | Strategyproof Learning with Advice. | Eric Balkanski, Cherlin Zhu |
| 2025 | Cost-Free Fairness in Online Correlation Clustering. | Eric Balkanski, Jason Chatzitheodorou, Andreas Maggiori |
| 2025 | Sample Compression Scheme Reductions. | Idan Attias, Steve Hanneke, Arvind Ramaswami |
| 2025 | Understanding Aggregations of Proper Learners in Multiclass Classification. | Julian Asilis, Mikael Mller Hgsgaard, Grigoris Velegkas |
| 2025 | Proper Learnability and the Role of Unlabeled Data. | Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng |
| 2025 | Refining the Sample Complexity of Comparative Learning. | Sajad Ashkezari, Ruth Urner |
| 2025 | Agnostic Private Density Estimation for GMMs via List Global Stability. | Mohammad Afzali, Hassan Ashtiani, Christopher Liaw |