| 2024 | Vector Quantile Regression on Manifolds. | Marco Pegoraro, Sanketh Vedula, Aviv Rosenberg, Irene Tallini, Emanuele Rodol, Alex M. Bronstein |
| 2024 | Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. | Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng |
| 2024 | Simulation-Free Schrdinger Bridges via Score and Flow Matching. | Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio |
| 2024 | Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games. | Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng |
| 2024 | Equivalence Testing: The Power of Bounded Adaptivity. | Diptarka Chakraborty, Sourav Chakraborty, Gunjan Kumar, Kuldeep S. Meel |
| 2023 | Nonstochastic Contextual Combinatorial Bandits. | Lukas Zierahn, Dirk van der Hoeven, Nicol Cesa-Bianchi, Gergely Neu |
| 2023 | Weather2K: A Multivariate Spatio-Temporal Benchmark Dataset for Meteorological Forecasting Based on Real-Time Observation Data from Ground Weather Stations. | Xun Zhu, Yutong Xiong, Ming Wu, Gaozhen Nie, Bin Zhang, Ziheng Yang |
| 2023 | Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation. | Yaxuan Zhu, Jianwen Xie, Ping Li |
| 2023 | Byzantine-Robust Federated Learning with Optimal Statistical Rates. | Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan |
| 2023 | Provably Efficient Reinforcement Learning via Surprise Bound. | Hanlin Zhu, Ruosong Wang, Jason D. Lee |
| 2023 | Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach. | Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li |
| 2023 | Domain Adaptation under Missingness Shift. | Helen Zhou, Sivaraman Balakrishnan, Zachary C. Lipton |
| 2023 | On the Consistency Rate of Decision Tree Learning Algorithms. | Qin-Cheng Zheng, Shen-Huan Lyu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou |
| 2023 | Knowledge Acquisition for Human-In-The-Loop Image Captioning. | Ervine Zheng, Qi Yu, Rui Li, Pengcheng Shi, Anne R. Haake |
| 2023 | Fair Representation Learning with Unreliable Labels. | Yixuan Zhang, Feng Zhou, Zhidong Li, Yang Wang, Fang Chen |
| 2023 | Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks. | Huishuai Zhang, Da Yu, Yiping Lu, Di He |
| 2023 | Spread Flows for Manifold Modelling. | Mingtian Zhang, Yitong Sun, Chen Zhang, Steven McDonagh |
| 2023 | Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision. | Jieyu Zhang, Linxin Song, Alex Ratner |
| 2023 | Conformal Off-Policy Prediction. | Yingying Zhang, Chengchun Shi, Shikai Luo |
| 2023 | Continuous-Time Decision Transformer for Healthcare Applications. | Zhiyue Zhang, Hongyuan Mei, Yanxun Xu |
| 2023 | Risk Bounds on Aleatoric Uncertainty Recovery. | Yikai Zhang, Jiahe Lin, Fengpei Li, Yeshaya Adler, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka |
| 2023 | Improved Bound on Generalization Error of Compressed KNN Estimator. | Hang Zhang, Ping Li |
| 2023 | Online Learning for Non-monotone DR-Submodular Maximization: From Full Information to Bandit Feedback. | Qixin Zhang, Zengde Deng, Zaiyi Chen, Kuangqi Zhou, Haoyuan Hu, Yu Yang |
| 2023 | Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis. | Xianyang Zhang, Trisha Dawn |
| 2023 | No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution. | Mengxiao Zhang, Shi Chen, Haipeng Luo, Yingfei Wang |