| 2025 | AxlePro: Momentum-Accelerated Batched Training of Kernel Machines. | Yiming Zhang, Parthe Pandit |
| 2025 | Personalizing Low-Rank Bayesian Neural Networks Via Federated Learning. | Boning Zhang, Dongzhu Liu, Osvaldo Simeone, Guanchu Wang, Dimitrios Pezaros, Guangxu Zhu |
| 2025 | Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning. | Jiaru Zhang, Rui Ding, Qiang Fu, Bojun Huang, Zizhen Deng, Yang Hua, Haibing Guan, Shi Han, Dongmei Zhang |
| 2025 | Truncated Inverse-Lvy Measure Representation of the Beta Process. | Junyi Zhang, Angelos Dassios, Zhong Chong, Qiufei Yao |
| 2025 | Robust Multi-fidelity Bayesian Optimization with Deep Kernel and Partition. | Fengxue Zhang, Thomas Desautels, Yuxin Chen |
| 2025 | Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory. | Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla |
| 2025 | On the Power of Adaptive Weighted Aggregation in Heterogeneous Federated Learning and Beyond. | Dun Zeng, Zenglin Xu, Shiyu Liu, Yu Pan, Qifan Wang, Xiaoying Tang |
| 2025 | Learning in Herding Mean Field Games: Single-Loop Algorithm with Finite-Time Convergence Analysis. | Sihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra Ganesh |
| 2025 | Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments. | Houssam Zenati, Judith Abcassis, Julie Josse, Bertrand Thirion |
| 2025 | Locally Private Sampling with Public Data. | Behnoosh Zamanlooy, Mario Daz, Shahab Asoodeh |
| 2025 | Knowledge Graph Completion with Mixed Geometry Tensor Factorization. | Viacheslav Yusupov, Maxim V. Rakhuba, Evgeny Frolov |
| 2025 | Evidential Uncertainty Probes for Graph Neural Networks. | Linlin Yu, Kangshuo Li, Pritom Kumar Saha, Yifei Lou, Feng Chen |
| 2025 | On the Sample Complexity of Next-Token Prediction. | Oguz Kaan Yksel, Nicolas Flammarion |
| 2025 | New User Event Prediction Through the Lens of Causal Inference. | Henry Shaowu Yuchi, Shixiang Zhu, Li Dong, Yigit M. Arisoy, Matthew C. Spencer |
| 2025 | Proximal Sampler with Adaptive Step Size. | Bo Yuan, Jiaojiao Fan, Jiaming Liang, Yongxin Chen |
| 2025 | Distributional Counterfactual Explanations With Optimal Transport. | Lei You, Lele Cao, Mattias Nilsson, Bo Zhao, Lei Lei |
| 2025 | Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models. | Haotian Ye, Himanshu Jain, Chong You, Ananda Theertha Suresh, Haowei Lin, James Zou, Felix X. Yu |
| 2025 | Locally Optimal Descent for Dynamic Stepsize Scheduling. | Gilad Yehudai, Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain |
| 2025 | Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability. | Zhuorui Ye, Farzan Farnia |
| 2025 | Causal discovery in mixed additive noise models. | Ruicong Yao, Tim Verdonck, Jakob Raymaekers |
| 2025 | Large Covariance Matrix Estimation With Nonnegative Correlations. | Yixin Yan, Qiao Yang, Ziping Zhao |
| 2025 | Understanding Expert Structures on Minimax Parameter Estimation in Contaminated Mixture of Experts. | Fanqi Yan, Huy Nguyen, Le Quang Dung, Pedram Akbarian, Nhat Ho |
| 2025 | Improved dependence on coherence in eigenvector and eigenvalue estimation error bounds. | Hao Yan, Keith Levin |
| 2025 | Testing Conditional Independence with Deep Neural Network Based Binary Expansion Testing (DeepBET). | Yang Yang, Kai Zhang, Ping-Shou Zhong |
| 2025 | Faster WIND: Accelerating Iterative Best-of-N Distillation for LLM Alignment. | Tong Yang, Jincheng Mei, Hanjun Dai, Zixin Wen, Shicong Cen, Dale Schuurmans, Yuejie Chi, Bo Dai |