| 2023 | Asymptotic confidence sets for random linear programs. | Shuyu Liu, Florentina Bunea, Jonathan Niles-Weed |
| 2023 | Improved Bounds for Multi-task Learning with Trace Norm Regularization. | Weiwei Liu |
| 2023 | ℓ | Yi Li, Honghao Lin, David P. Woodruff |
| 2023 | Allocating Divisible Resources on Arms with Unknown and Random Rewards. | Wenhao Li, Ningyuan Chen |
| 2023 | Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems. | Yunwen Lei |
| 2023 | A Lower Bound for Linear and Kernel Regression with Adaptive Covariates. | Tor Lattimore |
| 2023 | A Second-Order Method for Stochastic Bandit Convex Optimisation. | Tor Lattimore, Andrs Gyrgy |
| 2023 | Bagging is an Optimal PAC Learner. | Kasper Green Larsen |
| 2023 | A Pretty Fast Algorithm for Adaptive Private Mean Estimation. | Rohith Kuditipudi, John C. Duchi, Saminul Haque |
| 2023 | Is Planted Coloring Easier than Planted Clique? | Pravesh Kothari, Santosh S. Vempala, Alexander S. Wein, Jeff Xu |
| 2023 | Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators. | Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala |
| 2023 | Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm. | Fang Kong, Canzhe Zhao, Shuai Li |
| 2023 | U-Calibration: Forecasting for an Unknown Agent. | Bobby Kleinberg, Renato Paes Leme, Jon Schneider, Yifeng Teng |
| 2023 | Semi-Random Sparse Recovery in Nearly-Linear Time. | Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian |
| 2023 | A Nearly Tight Bound for Fitting an Ellipsoid to Gaussian Random Points. | Daniel Kane, Ilias Diakonikolas |
| 2023 | Learning and Testing Latent-Tree Ising Models Efficiently. | Anthimos Vardis Kandiros, Constantinos Daskalakis, Yuval Dagan, Davin Choo |
| 2023 | Deterministic Nonsmooth Nonconvex Optimization. | Michael I. Jordan, Guy Kornowski, Tianyi Lin, Ohad Shamir, Manolis Zampetakis |
| 2023 | Moments, Random Walks, and Limits for Spectrum Approximation. | Yujia Jin, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh |
| 2023 | Entropic characterization of optimal rates for learning Gaussian mixtures. | Zeyu Jia, Yury Polyanskiy, Yihong Wu |
| 2023 | Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence. | Ruichen Jiang, Qiujiang Jin, Aryan Mokhtari |
| 2023 | Tighter PAC-Bayes Bounds Through Coin-Betting. | Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij, Francesco Orabona |
| 2023 | Empirical Bayes via ERM and Rademacher complexities: the Poisson model. | Soham Jana, Yury Polyanskiy, Anzo Z. Teh, Yihong Wu |
| 2023 | Best-of-Three-Worlds Linear Bandit Algorithm with Variance-Adaptive Regret Bounds. | Shinji Ito, Kei Takemura |
| 2023 | Asymptotically Optimal Generalization Error Bounds for Noisy, Iterative Algorithms. | Ibrahim Issa, Amedeo Roberto Esposito, Michael Gastpar |
| 2023 | Minimizing Dynamic Regret on Geodesic Metric Spaces. | Zihao Hu, Guanghui Wang, Jacob D. Abernethy |