| 2023 | A High-dimensional Convergence Theorem for U-statistics with Applications to Kernel-based Testing. | Kevin Han Huang, Xing Liu, Andrew B. Duncan, Axel Gandy |
| 2023 | Reaching Kesten-Stigum Threshold in the Stochastic Block Model under Node Corruptions. | Yiding Hua, Jingqiu Ding, Tommaso d'Orsi, David Steurer |
| 2023 | Towards a Complete Analysis of Langevin Monte Carlo: Beyond Poincar Inequality. | Alireza Mousavi-Hosseini, Tyler K. Farghly, Ye He, Krishna Balasubramanian, Murat A. Erdogdu |
| 2023 | The Computational Complexity of Finding Stationary Points in Non-Convex Optimization. | Alexandros Hollender, Emmanouil Zampetakis |
| 2023 | A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs. | Dirk van der Hoeven, Lukas Zierahn, Tal Lancewicki, Aviv Rosenberg, Nicol Cesa-Bianchi |
| 2023 | Algorithmically Effective Differentially Private Synthetic Data. | Yiyun He, Roman Vershynin, Yizhe Zhu |
| 2023 | Optimal Scoring Rules for Multi-dimensional Effort. | Jason D. Hartline, Liren Shan, Yingkai Li, Yifan Wu |
| 2023 | Universal Rates for Multiclass Learning. | Steve Hanneke, Shay Moran, Qian Zhang |
| 2023 | Multiclass Online Learning and Uniform Convergence. | Steve Hanneke, Shay Moran, Vinod Raman, Unique Subedi, Ambuj Tewari |
| 2023 | Limits of Model Selection under Transfer Learning. | Steve Hanneke, Samory Kpotufe, Yasaman Mahdaviyeh |
| 2023 | Bandit Learnability can be Undecidable. | Steve Hanneke, Liu Yang |
| 2023 | Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms. | Osama A. Hanna, Lin Yang, Christina Fragouli |
| 2023 | Weak Recovery Threshold for the Hypergraph Stochastic Block Model. | Yuzhou Gu, Yury Polyanskiy |
| 2023 | Uniqueness of BP fixed point for the Potts model and applications to community detection. | Yuzhou Gu, Yury Polyanskiy |
| 2023 | Online Nonconvex Optimization with Limited Instantaneous Oracle Feedback. | Ziwei Guan, Yi Zhou, Yingbin Liang |
| 2023 | Non-asymptotic convergence bounds for Sinkhorn iterates and their gradients: a coupling approach. | Giacomo Greco, Maxence Noble, Giovanni Conforti, Alain Durmus |
| 2023 | Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler. | Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian |
| 2023 | The Expressive Power of Tuning Only the Normalization Layers. | Angeliki Giannou, Shashank Rajput, Dimitris Papailiopoulos |
| 2023 | Ticketed Learning-Unlearning Schemes. | Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang |
| 2023 | Minimax optimal testing by classification. | Patrik R. Gerber, Yanjun Han, Yury Polyanskiy |
| 2023 | Community Detection in the Hypergraph SBM: Optimal Recovery Given the Similarity Matrix. | Julia Gaudio, Nirmit Joshi |
| 2023 | Projection-free Online Exp-concave Optimization. | Dan Garber, Ben Kretzu |
| 2023 | Universality of Langevin Diffusion for Private Optimization, with Applications to Sampling from Rashomon Sets. | Arun Ganesh, Abhradeep Thakurta, Jalaj Upadhyay |
| 2023 | Geometric Barriers for Stable and Online Algorithms for Discrepancy Minimization. | David Gamarnik, Eren C. Kizildag, Will Perkins, Changji Xu |
| 2023 | Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization. | Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro |