| 2025 | MSP-SR: Multi-Stage Probabilistic Generative Super Resolution with Scarce High-Resolution Data. | Ruike Zhu, Matthew Charles Weston, Hanwen Zhang, Arindam Banerjee |
| 2025 | Collapsing Sequence-Level Data-Policy Coverage via Poisoning Attack in Offline Reinforcement Learning. | Xue Zhou, Dapeng Man, Chen Xu, Fanyi Zeng, Tao Liu, Huan Wang, Shucheng He, Chaoyang Gao, Wu Yang |
| 2025 | Learning to Sample in Stochastic Optimization. | Sijia Zhou, Yunwen Lei, Ata Kabn |
| 2025 | Sample and Computationally Efficient Continuous-Time Reinforcement Learning with General Function Approximation. | Runze Zhao, Yue Yu, Adams Yiyue Zhu, Chen Yang, Dongruo Zhou |
| 2025 | Towards Provably Efficient Learning of Imperfect Information Extensive-Form Games with Linear Function Approximation. | Canzhe Zhao, Shuze Chen, Weiming Liu, Haobo Fu, Qiang Fu, Shuai Li |
| 2025 | Improving Adversarial Transferability via Decision Boundary Adaptation. | Jiayu Zhang, Zhiyu Zhu, Zhibo Jin, Xinyi Wang, Huaming Chen, Kim-Kwang Raymond Choo |
| 2025 | Near-Optimal Regret Bounds for Federated Multi-armed Bandits with Fully Distributed Communication. | Haoran Zhang, Xuchuang Wang, Hao-Xu Chen, Hao Qiu, Lin Yang, Yang Gao |
| 2025 | Label Distribution Learning using the Squared Neural Family on the Probability Simplex. | Daokun Zhang, Russell Tsuchida, Dino Sejdinovic |
| 2025 | Learning to Stabilize Unknown LTI Systems on a Single Trajectory under Stochastic Noise. | Ziyi Zhang, Yorie Nakahira, Guannan Qu |
| 2025 | Finding Interior Optimum of Black-box Constrained Objective with Bayesian Optimization. | Fengxue Zhang, Yuxin Chen |
| 2025 | Residual Reweighted Conformal Prediction for Graph Neural Networks. | Zheng Zhang, Jie Bao, Zhixin Zhou, Nicol Colombo, Lixin Cheng, Rui Luo |
| 2025 | Instance-Wise Monotonic Calibration by Constrained Transformation. | Yunrui Zhang, Gustavo Enrique Batista, Salil S. Kanhere |
| 2025 | Causal Eligibility Traces for Confounding Robust Off-Policy Evaluation. | Junzhe Zhang, Elias Bareinboim |
| 2025 | Complete Characterization for Adjustment in Summary Causal Graphs of Time Series. | Clment Yvernes, Emilie Devijver, ric Gaussier |
| 2025 | How Likely Are Two Voting Rules Different? | Ziqi Yu, Lirong Xia, Qishen Han, Chengkai Zhang |
| 2025 | Corruption-Robust Variance-aware Algorithms for Generalized Linear Bandits under Heavy-tailed Rewards. | Qingyuan Yu, Euijin Baek, Xiang Li, Qiang Sun |
| 2025 | σ-Maximal Ancestral Graphs. | Binghua Yao, Joris M. Mooij |
| 2025 | MSCGrapher: Learning Multi-Scale Dynamic Correlations for Multivariate Time Series Forecasting. | Xian Yang, Zhenguo Zhang, Shihao Lu |
| 2025 | Best Arm Identification with Possibly Biased Offline Data. | Le Yang, Vincent Y. F. Tan, Wang Chi Cheung |
| 2025 | Flow-Based Delayed Hawkes Process. | Chao Yang, Wendi Ren, Shuang Li |
| 2025 | Full Network Capacity Framework for Sample-Efficient Deep Reinforcement Learning. | Wentao Yang, Xinyue Liu, Yunlong Gao, Wenxin Liang, Linlin Zong, Guanglu Wang, Xianchao Zhang |
| 2025 | Dependent Randomized Rounding for Budget Constrained Experimental Design. | Khurram Yamin, Edward Kennedy, Bryan Wilder |
| 2025 | Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling. | Jian Xu, Shian Du, Junmei Yang, Qianli Ma, Delu Zeng, John Paisley |
| 2025 | Learning Multi-interest Embedding with Dynamic Graph Cluster for Sequention Recommendation. | Chunjing Xiao, Ranhao Guo, Zhang Yongwang, Xiaoming Wu |
| 2025 | The Consistency Hypothesis in Uncertainty Quantification for Large Language Models. | Quan Xiao, Debarun Bhattacharjya, Balaji Ganesan, Radu Marinescu, Katsiaryna Mirylenka, Nhan H. Pham, Michael R. Glass, Junkyu Lee |