Li, Yingru

14 publications

NeurIPS 2025 OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation Mengkang Hu, Yuhang Zhou, Wendong Fan, Yuzhou Nie, Ziyu Ye, Bowei Xia, Tao Sun, Zhaoxuan Jin, Yingru Li, Zeyu Zhang, Yifeng Wang, Qianshuo Ye, Bernard Ghanem, Ping Luo, Guohao Li

NeurIPS 2025 Scalable Exploration via Ensemble++ Yingru Li, Jiawei Xu, Baoxiang Wang, Zhi-Quan Luo

ICLRW 2025 Scalable Thompson Sampling via Ensemble++ Yingru Li, Jiawei Xu, Baoxiang Wang, Zhi-Quan Luo

ICLRW 2025 Scaling Flaws of Verifier-Guided Search in Mathematical Reasoning Fei Yu, Yingru Li, Benyou Wang

ICMLW 2024 Adaptive Foundation Models for Online Decisions: HyperAgent with Fast Incremental Uncertainty Estimation Yingru Li, Jiawei Xu, Zhi-Quan Luo

ICMLW 2024 GPT-HyperAgent: Scalable Uncertainty Estimation and Exploration for Foundation Model Decisions Yingru Li, Jiawei Xu, Zhi-Quan Luo

AISTATS 2024 Prior-Dependent Analysis of Posterior Sampling Reinforcement Learning with Function Approximation Yingru Li, Zhiquan Luo

ICMLW 2024 Probability Tools for Sequential Random Projection Yingru Li

ICML 2024 Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent Yingru Li, Jiawei Xu, Lei Han, Zhi-Quan Luo

ICMLW 2024 Simple, Unified Analysis of Johnson-Lindenstrauss with Applications Yingru Li

NeurIPSW 2023 Efficient and Scalable Reinforcement Learning via Hypermodel Yingru Li, Jiawei Xu, Zhi-Quan Luo

ICMLW 2023 Optimistic Thompson Sampling for No-Regret Learning in Unknown Games Yingru Li, Liangqi Liu, Wenqiang Pu, Zhi-Quan Luo

ICLR 2022 HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning Ziniu Li, Yingru Li, Yushun Zhang, Tong Zhang, Zhi-Quan Luo

NeurIPS 2019 Divergence-Augmented Policy Optimization Qing Wang, Yingru Li, Jiechao Xiong, Tong Zhang