| 2025 | Post-processing for Fair Regression via Explainable SVD. | Zhiqun Zuo, Ding Zhu, Mohammad Mahdi Khalili |
| 2025 | Almost linear time differentially private release of synthetic graphs. | Zongrui Zou, Jingcheng Liu, Jalaj Upadhyay |
| 2025 | Theoretical Analysis of Leave-one-out Cross Validation for Non-differentiable Penalties under High-dimensional Settings. | Haolin Zou, Arnab Auddy, Kamiar Rahnama Rad, Arian Maleki |
| 2025 | Time-varying Gaussian Process Bandits with Unknown Prior. | Juliusz Ziomek, Masaki Adachi, Michael A. Osborne |
| 2025 | Conditional Generative Learning from Invariant Representations in Multi-Source: Robustness and Efficiency. | Guojun Zhu, Sanguo Zhang, Mingyang Ren |
| 2025 | Learning to Negotiate via Voluntary Commitment. | Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart |
| 2025 | Protein Fitness Landscape: Spectral Graph Theory Perspective. | Hao Zhu, Daniel M. Steinberg, Piotr Koniusz |
| 2025 | Near-Polynomially Competitive Active Logistic Regression. | Yihan Zhou, Eric Price, Trung Nguyen |
| 2025 | Bridging Domains with Approximately Shared Features. | Ziliang Samuel Zhong, Xiang Pan, Qi Lei |
| 2025 | Models That Are Interpretable But Not Transparent. | Chudi Zhong, Panyu Chen, Cynthia Rudin |
| 2025 | Nonparametric Factor Analysis and Beyond. | Yujia Zheng, Yang Liu, Jiaxiong Yao, Yingyao Hu, Kun Zhang |
| 2025 | HAR-former: Hybrid Transformer with an Adaptive Time-Frequency Representation Matrix for Long-Term Series Forecasting. | Kenghao Zheng, Zi Long, Shuxin Wang |
| 2025 | Multi-level Advantage Credit Assignment for Cooperative Multi-Agent Reinforcement Learning. | Xutong Zhao, Yaqi Xie |
| 2025 | Noisy Low-Rank Matrix Completion via Transformed L | Kun Zhao, Jiayi Wang, Yifei Lou |
| 2025 | Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models. | Siyan Zhao, Daniel Israel, Guy Van den Broeck, Aditya Grover |
| 2025 | Cubic regularized subspace Newton for non-convex optimization. | Jim Zhao, Nikita Doikov, Aurlien Lucchi |
| 2025 | From Deep Additive Kernel Learning to Last-Layer Bayesian Neural Networks via Induced Prior Approximation. | Wenyuan Zhao, Haoyuan Chen, Tie Liu, Rui Tuo, Chao Tian |
| 2025 | Analyzing the Role of Permutation Invariance in Linear Mode Connectivity. | Keyao Zhan, Puheng Li, Lei Wu |
| 2025 | What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization. | Yufeng Zhang, Fengzhuo Zhang, Zhuoran Yang, Zhaoran Wang |
| 2025 | Recurrent Neural Goodness-of-Fit Test for Time Series. | Aoran Zhang, Wenbin Zhou, Liyan Xie, Shixiang Zhu |
| 2025 | Understanding Inverse Reinforcement Learning under Overparameterization: Non-Asymptotic Analysis and Global Optimality. | Ruijia Zhang, Siliang Zeng, Chenliang Li, Alfredo Garca, Mingyi Hong |
| 2025 | Your Finetuned Large Language Model is Already a Powerful Out-of-distribution Detector. | Andi Zhang, Tim Z. Xiao, Weiyang Liu, Robert Bamler, Damon Wischik |
| 2025 | Restructuring Tractable Probabilistic Circuits. | Honghua Zhang, Benjie Wang, Marcelo Arenas, Guy Van den Broeck |
| 2025 | Generalization Lower Bounds for GD and SGD in Smooth Stochastic Convex Optimization. | Peiyuan Zhang, Jiaye Teng, Jingzhao Zhang |
| 2025 | Quantile Additive Trend Filtering. | Zhi Zhang, Kyle Ritscher, Oscar Hernan Madrid Padilla |