| 2024 | Low-degree phase transitions for detecting a planted clique in sublinear time. | Jay Mardia, Kabir Aladin Verchand, Alexander S. Wein |
| 2024 | Harmonics of Learning: Universal Fourier Features Emerge in Invariant Networks. | Giovanni Luca Marchetti, Christopher J. Hillar, Danica Kragic, Sophia Sanborn |
| 2024 | Projection by Convolution: Optimal Sample Complexity for Reinforcement Learning in Continuous-Space MDPs. | Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli |
| 2024 | Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion. | Jianhao Ma, Salar Fattahi |
| 2024 | Linear bandits with polylogarithmic minimax regret. | Josep Lumbreras, Marco Tomamichel |
| 2024 | Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics. | Brendan Lucier, Sarath Pattathil, Aleksandrs Slivkins, Mengxiao Zhang |
| 2024 | The Predicted-Updates Dynamic Model: Offline, Incremental, and Decremental to Fully Dynamic Transformations. | Quanquan C. Liu, Vaidehi Srinivas |
| 2024 | Spatial properties of Bayesian unsupervised trees. | Linxi Liu, Li Ma |
| 2024 | The role of randomness in quantum state certification with unentangled measurements. | Yuhan Liu, Jayadev Acharya |
| 2024 | Online Policy Optimization in Unknown Nonlinear Systems. | Yiheng Lin, James A. Preiss, Fengze Xie, Emile Anand, Soon-Jo Chung, Yisong Yue, Adam Wierman |
| 2024 | Optimistic Rates for Learning from Label Proportions. | Gene Li, Lin Chen, Adel Javanmard, Vahab Mirrokni |
| 2024 | Follow-the-Perturbed-Leader with Frchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds. | Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh |
| 2024 | Inherent limitations of dimensions for characterizing learnability of distribution classes. | Tosca Lechner, Shai Ben-David |
| 2024 | Better-than-KL PAC-Bayes Bounds. | Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona |
| 2024 | Accelerated Parameter-Free Stochastic Optimization. | Itai Kreisler, Maor Ivgi, Oliver Hinder, Yair Carmon |
| 2024 | Simple online learning with consistent oracle. | Alexander Kozachinskiy, Tomasz Steifer |
| 2024 | Open Problem: Anytime Convergence Rate of Gradient Descent. | Guy Kornowski, Ohad Shamir |
| 2024 | Sampling from the Mean-Field Stationary Distribution. | Yunbum Kook, Matthew Shunshi Zhang, Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li |
| 2024 | Gaussian Cooling and Dikin Walks: The Interior-Point Method for Logconcave Sampling. | Yunbum Kook, Santosh S. Vempala |
| 2024 | Convergence of Kinetic Langevin Monte Carlo on Lie groups. | Lingkai Kong, Molei Tao |
| 2024 | Superconstant Inapproximability of Decision Tree Learning. | Caleb Koch, Carmen Strassle, Li-Yang Tan |
| 2024 | Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds. | Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2024 | Testable Learning with Distribution Shift. | Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2024 | Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps. | Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi |
| 2024 | Choosing the p in Lp Loss: Adaptive Rates for Symmetric Mean Estimation. | Yu-Chun Kao, Min Xu, Cun-Hui Zhang |