ML Anthology

Li, Na

38 publications

AISTATS 2025 Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored Data Hongni Wang, Junxi Zhang, Na Li, Linglong Kong, Bei Jiang, Xiaodong Yan
NeurIPS 2025 Constrained Optimization from a Control Perspective via Feedback Linearization Runyu Zhang, Arvind Raghunathan, Jeff S Shamma, Na Li
L4DC 2025 Efficient Duple Perturbation Robustness in Low-Rank MDPs Yang Hu, Haitong Ma, Na Li, Bo Dai
ICML 2025 Efficient Online Reinforcement Learning for Diffusion Policy Haitong Ma, Tianyi Chen, Kai Wang, Na Li, Bo Dai
AISTATS 2025 Primal-Dual Spectral Representation for Off-Policy Evaluation Yang Hu, Tianyi Chen, Na Li, Kai Wang, Bo Dai
NeurIPS 2025 RODS: Robust Optimization Inspired Diffusion Sampling for Detecting and Reducing Hallucination in Generative Models Yiqi Tian, Pengfei Jin, Mingze Yuan, Na Li, Bo Zeng, Quanzheng Li
NeurIPS 2025 Sample-Efficient Tabular Self-Play for Offline Robust Reinforcement Learning Na Li, Zewu Zheng, Wei Ni, Hangguan Shan, Wenjie Zhang, Xinyu Li
AISTATS 2025 Scalable Spectral Representations for Multiagent Reinforcement Learning in Network MDPs Zhaolin Ren, Runyu Zhang, Bo Dai, Na Li
ECML-PKDD 2025 Target-Adaptive Structure-Semantic Consistency for Unsupervised Graph Domain Adaptation Yan Zou, Yongzheng Lu, Na Li, Xiatian Zhu, Lan Du, Ming Yan, Ying Ma
NeurIPS 2024 Enhancing Preference-Based Linear Bandits via Human Response Time Shen Li, Yuyang Zhang, Zhaolin Ren, Claire Liang, Na Li, Julie A. Shah
ICML 2024 Learning Low-Dimensional Latent Dynamics from High-Dimensional Observations: Non-Asymptotics and Lower Bounds Yuyang Zhang, Shahriar Talebi, Na Li
L4DC 2024 MPC-Inspired Reinforcement Learning for Verifiable Model-Free Control Yiwen Lu, Zishuo Li, Yihan Zhou, Na Li, Yilin Mo
L4DC 2024 Multi-Agent Coverage Control with Transient Behavior Consideration Runyu Zhang, Haitong Ma, Na Li
ICLR 2024 Provable Memory Efficient Self-Play Algorithm for Model-Free Reinforcement Learning Na Li, Yuchen Jiao, Hangguan Shan, Shefeng Yan
ICLR 2024 Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity Runyu Zhang, Yang Hu, Na Li
ICML 2023 Escaping Saddle Points in Zeroth-Order Optimization: The Power of Two-Point Estimators Zhaolin Ren, Yujie Tang, Na Li
ICLR 2023 FedDAR: Federated Domain-Aware Representation Learning Aoxiao Zhong, Hao He, Zhaolin Ren, Na Li, Quanzheng Li
ICLR 2023 Latent Variable Representation for Reinforcement Learning Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai
AISTATS 2023 Learning to Optimize with Stochastic Dominance Constraints Hanjun Dai, Yuan Xue, Niao He, Yixin Wang, Na Li, Dale Schuurmans, Bo Dai
L4DC 2023 Multi-Agent Reinforcement Learning with Reward Delays Yuyang Zhang, Runyu Zhang, Yuantao Gu, Na Li
L4DC 2023 On Controller Reduction in Linear Quadratic Gaussian Control with Performance Bounds Zhaolin Ren, Yang Zheng, Maryam Fazel, Na Li
L4DC 2023 Online Switching Control with Stability and Regret Guarantees Yingying Li, James A Preiss, Na Li, Yiheng Lin, Adam Wierman, Jeff S Shamma
ICML 2022 Improve Single-Point Zeroth-Order Optimization Using High-Pass and Low-Pass Filters Xin Chen, Yujie Tang, Na Li
NeurIPS 2022 On the Global Convergence Rates of Decentralized SoftMax Gradient Play in Markov Potential Games Runyu Zhang, Jincheng Mei, Bo Dai, Dale Schuurmans, Na Li
NeurIPS 2022 Policy Optimization for Markov Games: Unified Framework and Faster Convergence Runyu Zhang, Qinghua Liu, Huan Wang, Caiming Xiong, Na Li, Yu Bai
L4DC 2021 Analysis of the Optimization Landscape of Linear Quadratic Gaussian (LQG) Control Yujie Tang, Yang Zheng, Na Li
IJCAI 2021 Modelling General Properties of Nouns by Selectively Averaging Contextualised Embeddings Na Li, Zied Bouraoui, José Camacho-Collados, Luis Espinosa Anke, Qing Gu, Steven Schockaert
AAAI 2021 Online Optimal Control with Affine Constraints Yingying Li, Subhro Das, Na Li
L4DC 2021 Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems Yang Zheng, Luca Furieri, Maryam Kamgarpour, Na Li
IJCAI 2020 Attention as Relation: Learning Supervised Multi-Head Self-Attention for Relation Extraction Jie Liu, Shaowei Chen, Bingquan Wang, Jiaxin Zhang, Na Li, Tong Xu
L4DC 2020 Distributed Reinforcement Learning for Decentralized Linear Quadratic Control: A Derivative-Free Policy Optimization Approach Yingying Li, Yujie Tang, Runyu Zhang, Na Li
NeurIPS 2020 Leveraging Predictions in Smoothed Online Convex Optimization via Gradient-Based Algorithms Yingying Li, Na Li
NeurIPS 2020 Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward Guannan Qu, Yiheng Lin, Adam Wierman, Na Li
L4DC 2020 Scalable Reinforcement Learning of Localized Policies for Multi-Agent Networked Systems Guannan Qu, Adam Wierman, Na Li
IJCAI 2019 Network Embedding with Dual Generation Tasks Jie Liu, Na Li, Zhicheng He
NeurIPS 2019 Online Optimal Control with Linear Dynamics and Predictions: Algorithms and Regret Analysis Yingying Li, Xin Chen, Na Li
IJCAI 2016 Incentivizing Reliability in Demand-Side Response Hongyao Ma, Valentin Robu, Na Li, David C. Parkes
ECCV 2010 What Is the Chance of Happening: A New Way to Predict Where People Look Yezhou Yang, Mingli Song, Na Li, Jiajun Bu, Chun Chen