Li Zhao

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 51

Top Topics

Traveling Salesman

Reinforcement Learning

Top Venues

Publications

Qingpeng Cai, Xiangyu Zhao, Ling Pan, Xin Xin, Jin Huang, Weinan Zhang, Li Zhao, Dawei Yin, Grace Hui Yang
AgentIR: 1st Workshop on Agent-based Information Retrieval. SIGIR (2024)
Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. ACL (1) (2024)
Guangran Cheng, Chuheng Zhang, Wenzhe Cai, Li Zhao, Changyin Sun, Jiang Bian
Empowering Large Language Models on Robotic Manipulation with Affordance Prompting. CoRR (2024)
Han Zhong, Guhao Feng, Wei Xiong, Li Zhao, Di He, Jiang Bian, Liwei Wang
DPO Meets PPO: Reinforced Token Optimization for RLHF. CoRR (2024)
Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. CoRR (2024)
Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian
Video In-context Learning. CoRR (2024)
Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian
Pre-Trained Large Language Models for Industrial Control. CoRR (2023)
Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, Jiang Bian
Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem. AAAI (2023)
Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, Jiang Bian
Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem. CoRR (2023)
Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. KDD (2023)
Chuheng Zhang, Yitong Duan, Xiaoyu Chen, Jianyu Chen, Jian Li, Li Zhao
Towards Generalizable Reinforcement Learning for Trade Execution. CoRR (2023)
Xuanhao Pan, Yan Jin, Yuandong Ding, Mingxiao Feng, Li Zhao, Lei Song, Jiang Bian
H-TSP: Hierarchically Solving the Large-Scale Traveling Salesman Problem. AAAI (2023)
Xin Xin, Xiangyu Zhao, Jin Huang, Weinan Zhang, Li Zhao, Dawei Yin, Grace Hui Yang
DRL4IR: 4th Workshop on Deep Reinforcement Learning for Information Retrieval. CIKM (2023)
Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. CoRR (2023)
Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley Llorens
Distributional Pareto-Optimal Multi-Objective Reinforcement Learning. NeurIPS (2023)
Yuanying Cai, Chuheng Zhang, Hanye Zhao, Li Zhao, Jiang Bian
Curriculum Offline Reinforcement Learning. AAMAS (2023)
Jinpeng Zhang, Yufeng Zheng, Chuheng Zhang, Li Zhao, Lei Song, Yuan Zhou, Jiang Bian
Robust Situational Reinforcement Learning in Face of Context Disturbances. ICML (2023)
Xiangyu Zhao, Xin Xin, Weinan Zhang, Li Zhao, Dawei Yin, Grace Hui Yang
DRL4IR: 3rd Workshop on Deep Reinforcement Learning for Information Retrieval. SIGIR (2022)
Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. CoRR (2022)
Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu
An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context. NeurIPS (2022)
Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, Tieyan Liu
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets. CoRR (2022)
Guoqing Liu, Mengzhang Cai, Li Zhao, Tao Qin, Adrian Brown, Jimmy Bischoff, Tie-Yan Liu
Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation. CoG (2022)
Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. NeurIPS (2022)
Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. ICLR (2022)
Guoqing Liu, Mengzhang Cai, Li Zhao, Tao Qin, Adrian Brown, Jimmy Bischoff, Tie-Yan Liu
Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation. CoRR (2022)
Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu
Curriculum Offline Imitating Learning. NeurIPS (2021)
Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu
Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. NeurIPS (2021)
Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
Demonstration actor critic. Neurocomputing 434 (2021)
Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu
Return-Based Contrastive Representation Learning for Reinforcement Learning. CoRR (2021)
Pushi Zhang, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, Tie-Yan Liu
Independence-aware Advantage Estimation. IJCAI (2021)
Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu
Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. CoRR (2021)
Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu
Return-Based Contrastive Representation Learning for Reinforcement Learning. ICLR (2021)
Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning. NeurIPS (2021)
Kangzhi Zhao, Xiting Wang, Yuren Zhang, Li Zhao, Zheng Liu, Chunxiao Xing, Xing Xie
Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs. SIGIR (2020)
Junjie Li, Sotetsu Koyamada, Qiwei Ye, Guoqing Liu, Chao Wang, Ruihan Yang, Li Zhao, Tao Qin, Tie-Yan Liu, Hsiao-Wuen Hon
Suphx: Mastering Mahjong with Deep Reinforcement Learning. CoRR (2020)
Zichuan Lin, Derek Yang, Li Zhao, Tao Qin, Guangwen Yang, Tie-Yan Liu
RD$^2$: Reward Decomposition with Representation Decomposition. NeurIPS (2020)
Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Guangwen Yang, Tie-Yan Liu
Distributional Reward Decomposition for Reinforcement Learning. CoRR (2019)
Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu
Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction. KDD (2019)
Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, Enhong Chen, Tie-Yan Liu
Semi-Supervised Neural Machine Translation via Marginal Distribution Estimation. IEEE ACM Trans. Audio Speech Lang. Process. 27 (10) (2019)
Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, Tie-Yan Liu, Guangwen Yang
Distributional Reward Decomposition for Reinforcement Learning. NeurIPS (2019)
Zichuan Lin, Li Zhao, Jiang Bian, Tao Qin, Guangwen Yang
Unified Policy Optimization for Robust Reinforcement Learning. ACML (2019)
Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu
Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding. KDD (2019)
Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. NeurIPS (2019)
Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, Tie-Yan Liu
Fully Parameterized Quantile Function for Distributional Reinforcement Learning. CoRR (2019)
Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
Trust Region Evolution Strategies. AAAI (2019)
Lijun Wu, Fei Tian, Li Zhao, Jianhuang Lai, Tie-Yan Liu
Word Attention for Sequence to Sequence Text Understanding. AAAI (2018)
Fei Gao, Lijun Wu, Li Zhao, Tao Qin, Xueqi Cheng, Tie-Yan Liu
Efficient Sequence Learning with Group Recurrent Networks. NAACL-HLT (2018)
Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, Guiquan Liu, Tie-Yan Liu
Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization. AAAI (2018)
Lijun Wu, Yingce Xia, Fei Tian, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu
Adversarial Neural Machine Translation. ACML (2018)
Lijun Wu, Li Zhao, Tao Qin, Jianhuang Lai, Tie-Yan Liu
Sequence Prediction with Unlabeled Data by Reward Function Learning. IJCAI (2017)
Lijun Wu, Yingce Xia, Li Zhao, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu
Adversarial Neural Machine Translation. CoRR (2017)