| 2025 | Enhancing Feature-Specific Data Protection via Bayesian Coordinate Differential Privacy. | Maryam Aliakbarpour, Syomantak Chaudhuri, Thomas A. Courtade, Alireza Fallah, Michael I. Jordan |
| 2025 | Privacy in Metalearning and Multitask Learning: Modeling and Separations. | Maryam Aliakbarpour, Konstantina Bairaktari, Adam Smith, Marika Swanberg, Jonathan R. Ullman |
| 2025 | Zero-Shot Action Generalization with Limited Observations. | Abdullah Alchihabi, Hanping Zhang, Yuhong Guo |
| 2025 | Survival Models: Proper Scoring Rule and Stochastic Optimization with Competing Risks. | Julie Alberge, Vincent Maladire, Olivier Grisel, Judith Abcassis, Gal Varoquaux |
| 2025 | Planning and Learning in Risk-Aware Restless Multi-Arm Bandits. | Nima Akbarzadeh, Yossiri Adulyasak, Erick Delage |
| 2025 | Distributional Adversarial Loss. | Saba Ahmadi, Siddharth Bhandari, Avrim Blum, Chen Dan, Prabhav Jain |
| 2025 | Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VI. | Abhinav Agrawal, Justin Domke |
| 2025 | Online-to-PAC generalization bounds under graph-mixing dependencies. | Baptiste Abls, Gergely Neu, Eugenio Clerico |
| 2024 | Near Optimal Adversarial Attacks on Stochastic Bandits and Defenses with Smoothed Responses. | Shiliang Zuo |
| 2024 | Multi-Dimensional Hyena for Spatial Inductive Bias. | Itamar Zimerman, Lior Wolf |
| 2024 | Robust Offline Reinforcement Learning with Heavy-Tailed Rewards. | Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi |
| 2024 | On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers. | Cai Zhou, Rose Yu, Yusu Wang |
| 2024 | Timing as an Action: Learning When to Observe and Act. | Helen Zhou, Audrey Huang, Kamyar Azizzadenesheli, David Childers, Zachary C. Lipton |
| 2024 | Reward-Relevance-Filtered Linear Offline Reinforcement Learning. | Angela Zhou |
| 2024 | Better Batch for Deep Probabilistic Time Series Forecasting. | Vincent Zhihao Zheng, Seongjin Choi, Lijun Sun |
| 2024 | Graph Machine Learning through the Lens of Bilevel Optimization. | Amber Yijia Zheng, Tong He, Yixuan Qiu, Minjie Wang, David Wipf |
| 2024 | Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo. | Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin |
| 2024 | DHMConv: Directed Hypergraph Momentum Convolution Framework. | Wenbo Zhao, Zitong Ma, Zhe Yang |
| 2024 | Positivity-free Policy Learning with Observational Data. | Pan Zhao, Antoine Chambaz, Julie Josse, Shu Yang |
| 2024 | Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent. | Jialun Zhang, Richard Y. Zhang, Hong-Ming Chiu |
| 2024 | HintMiner: Automatic Question Hints Mining From Q&A Web Posts with Language Model via Self-Supervised Learning. | Zhenyu Zhang, JiuDong Yang |
| 2024 | Optimal Sparse Survival Trees. | Rui Zhang, Rui Xin, Margo I. Seltzer, Cynthia Rudin |
| 2024 | Restricted Isometry Property of Rank-One Measurements with Random Unit-Modulus Vectors. | Wei Zhang, Zhenni Wang |
| 2024 | Membership Testing in Markov Equivalence Classes via Independence Queries. | Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler |
| 2024 | Formal Verification of Unknown Stochastic Systems via Non-parametric Estimation. | Zhi Zhang, Chenyu Ma, Saleh Soudijani, Sadegh Soudjani |