| 2025 | New Lower Bounds for Non-Convex Stochastic Optimization through Divergence Decomposition. | El Mehdi Saad, Wei-Cheng Lee, Francesco Orabona |
| 2025 | Improved Offline Contextual Bandits with Second-Order Bounds: Betting and Freezing. | Jongha Jon Ryu, Jeongyeol Kwon, Benjamin Koppe, Kwang-Sung Jun |
| 2025 | Capacity-Constrained Online Learning with Delays: Scheduling Frameworks and Regret Trade-offs. | Alexander Ryabchenko, Idan Attias, Daniel M. Roy |
| 2025 | Can a calibration metric be both testable and actionable? | Raphael Rossellini, Jake A. Soloff, Rina Foygel Barber, Zhimei Ren, Rebecca Willett |
| 2025 | Necessary and Sufficient Oracles: Toward a Computational Taxonomy for Reinforcement Learning. | Dhruv Rohatgi, Dylan J. Foster |
| 2025 | Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification (extended abstract). | Dhruv Rohatgi, Adam Block, Audrey Huang, Akshay Krishnamurthy, Dylan J. Foster |
| 2025 | Metric Clustering and Graph Optimization Problems using Weak Comparison Oracles. | Rahul Raychaudhury, Wen-Zhi Li, Syamantak Das, Sainyam Galhotra, Stavros Sintos |
| 2025 | Generation through the lens of learning theory. | Vinod Raman, Jiaxun Li, Ambuj Tewari |
| 2025 | Truthfulness of Decision-Theoretic Calibration Measures. | Mingda Qiao, Eric Zhao |
| 2025 | Linear Convergence of Diffusion Models Under the Manifold Hypothesis. | Peter Potaptchik, Iskander Azangulov, George Deligiannidis |
| 2025 | Lower Bounds for Private Estimation of Gaussian Covariance Matrices under All Reasonable Parameter Regimes. | Victor S. Portella, Nicholas J. A. Harvey |
| 2025 | Optimal Robust Estimation under Local and Global Corruptions: Stronger Adversary and Smaller Error. | Thanasis Pittas, Ankit Pensia |
| 2025 | Recovering Labels from Crowdsourced Data: an Optimal and Polynomial-Time Method. | Emmanuel Pilliat |
| 2025 | Differentially Private Synthetic Graphs Preserving Triangle-Motif Cuts. | Pan Peng, Hangyu Xu |
| 2025 | Learning Algorithms in the Limit. | Hristo Papazov, Nicolas Flammarion |
| 2025 | Data-dependent Bounds with T-Optimal Best-of-Both-Worlds Guarantees in Multi-Armed Bandits using Stability-Penalty Matching. | Quan M. Nguyen, Shinji Ito, Junpei Komiyama, Nishant A. Mehta |
| 2025 | Improved algorithms for learning quantum Hamiltonians, via flat polynomials. | Shyam Narayanan |
| 2025 | Estimating stationary mass, frequency by frequency. | Milind Nakul, Vidya Muthukumar, Ashwin Pananjady |
| 2025 | Sharper Bounds for Chebyshev Moment Matching, with Applications. | Cameron Musco, Christopher Musco, Lucas Rosenblatt, Apoorv Vikram Singh |
| 2025 | Are all models wrong? Fundamental limits in distribution-free empirical model falsification. | Manuel M. Mller, Yuetian Luo, Rina Foygel Barber |
| 2025 | Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning. | Antoine Moulin, Gergely Neu, Luca Viano |
| 2025 | Beyond Worst-Case Online Classification: VC-Based Regret Bounds for Relaxed Benchmarks. | Omar Montasser, Abhishek Shetty, Nikita Zhivotovskiy |
| 2025 | The Planted Spanning Tree Problems: Exact Overlap Characterization via Local Weak Convergence Extended Abstract. | Mehrdad Moharrami, Cristopher Moore, Jiaming Xu |
| 2025 | Sample and Oracle Efficient Reinforcement Learning for MDPs with Linearly-Realizable Value Functions. | Zakaria Mhammedi |
| 2025 | Online Convex Optimization with a Separation Oracle. | Zakaria Mhammedi |