Qu, Guannan

23 publications

TMLR 2026 Natural Policy Gradient for Average Reward Non-Stationary Reinforcement Learning Neharika Jali, Eshika Pathak, Pranay Sharma, Guannan Qu, Gauri Joshi

ICML 2025 A Theoretical Study of (Hyper) Self-Attention Through the Lens of Interactions: Representation, Training, Generalization Muhammed Ustaomeroglu, Guannan Qu

UAI 2025 Learning to Stabilize Unknown LTI Systems on a Single Trajectory Under Stochastic Noise Ziyi Zhang, Yorie Nakahira, Guannan Qu

NeurIPS 2025 Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning Emile Timothy Anand, Ishani Karmarkar, Guannan Qu

TMLR 2025 Predictive Control and Regret Analysis of Non-Stationary MDP with Look-Ahead Information Ziyi Zhang, Yorie Nakahira, Guannan Qu

NeurIPS 2025 Stabilizing LTI Systems Under Partial Observability: Sample Complexity and Fundamental Limits Ziyi Zhang, Yorie Nakahira, Guannan Qu

L4DC 2024 CoVO-MPC: Theoretical Analysis of Sampling-Based MPC and Optimal Covariance Design Zeji Yi, Chaoyi Pan, Guanqi He, Guannan Qu, Guanya Shi

L4DC 2024 Combining Model-Based Controller and ML Advice via Convex Reparameterization Junxuan Shen, Adam Wierman, Guannan Qu

AISTATS 2024 Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems Neharika Jali, Guannan Qu, Weina Wang, Gauri Joshi

ICML 2024 Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies Alex Deweese, Guannan Qu

ICMLW 2024 Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies Alex DeWeese, Guannan Qu

ICMLW 2024 Model Based Diffusion for Trajectory Optimization Chaoyi Pan, Zeji Yi, Guanya Shi, Guannan Qu

NeurIPS 2024 Model-Based Diffusion for Trajectory Optimization Chaoyi Pan, Zeji Yi, Guanya Shi, Guannan Qu

L4DC 2023 Compositional Neural Certificates for Networked Dynamical Systems Songyuan Zhang, Yumeng Xiu, Guannan Qu, Chuchu Fan

NeurIPS 2022 Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity Yiheng Lin, Yang Hu, Guannan Qu, Tongxin Li, Adam Wierman

ICML 2022 Decentralized Online Convex Optimization in Networked Systems Yiheng Lin, Judy Gan, Guannan Qu, Yash Kanoria, Adam Wierman

NeurIPS 2022 On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory Yang Hu, Adam Wierman, Guannan Qu

NeurIPS 2021 Multi-Agent Reinforcement Learning in Stochastic Networked Systems Yiheng Lin, Guannan Qu, Longbo Huang, Adam Wierman

NeurIPS 2021 Perturbation-Based Regret Analysis of Predictive Control in Linear Time Varying Systems Yiheng Lin, Yang Hu, Guanya Shi, Haoyuan Sun, Guannan Qu, Adam Wierman

L4DC 2021 Stable Online Control of Linear Time-Varying Systems Guannan Qu, Yuanyuan Shi, Sahin Lale, Anima Anandkumar, Adam Wierman

COLT 2020 Finite-Time Analysis of Asynchronous Stochastic Approximation and $q$-Learning Guannan Qu, Adam Wierman

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