Li Zhao - AI Profile

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Microsoft

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Her research interests mainly lie in deep learning and reinforcement learning, and their applications for text mining, finance, game and operations research.

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Papers26 papers

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Return-Based Contrastive Representation Learning for Reinforcement Learning

Guoqing Liu, Chuheng Zhang,Li Zhao,Tao Qin, Jinhua Zhu,Li Jian,Nenghai Yu,Tie-Yan Liu

ICLR, (2021)

EIBibtex

Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs

Kangzhi Zhao,Xiting Wang, Yuren Zhang,Li Zhao,Zheng Liu,Chunxiao Xing,Xing Xie

SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Re..., pp.239-248, (2020)

Cited by5EIBibtex

RD$2$ - Reward Decomposition with Representation Decomposition

Zichuan Lin, Derek Yang,Li Zhao,Tao Qin,Guangwen Yang,Tie-Yan Liu

NeurIPS, (2020)

EIBibtex

RD22^2: Reward Decomposition with Representation Decomposition

Zichuan Lin, Derek Yang,Li Zhao,Tao Qin,Guangwen Yang,Tie-Yan Liu

NIPS 2020, (2020)

Bibtex

Suphx: Mastering Mahjong with Deep Reinforcement Learning

Li Junjie, Koyamada Sotetsu, Ye Qiwei, Liu Guoqing, Wang Chao,Yang Ruihan,Zhao Li,Qin Tao,Liu Tie-Yan,Hon Hsiao-Wuen

Bibtex

Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction

Chen Chi,Zhao Li, Cao Wei, Bian Jiang, Xing Chunxiao

Bibtex

Demonstration Actor Critic

Guoqing Liu,Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu,Tie-Yan Liu

(2019)

Bibtex

Independence-aware Advantage Estimation

Pushi Zhang,Li Zhao, Guoqing Liu, Jiang Bian, Minglie Huang,Tao Qin,Tie-Yan Liu

(2019)

Bibtex

Distributional Reward Decomposition for Reinforcement Learning

Zichuan Lin,Li Zhao, Derek C Yang,Tao Qin,Tie-Yan Liu,Guangwen Yang

NeurIPS, pp.6212-6221, (2019)

Cited by2EIBibtex

Fully Parameterized Quantile Function for Distributional Reinforcement Learning

Derek C Yang,Li Zhao,Zichuan Lin,Tao Qin,Jiang Bian,Tie-Yan Liu

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), (2019): 6190-6199

Cited by16EIBibtex

Trust Region Evolution Strategies

Guoqing Liu,Li Zhao, Feidiao Yang,Jiang Bian,Tao Qin,Nenghai Yu,Tie-Yan Liu

THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF AR..., pp.4352-4359, (2019)

Cited by13EIBibtex

Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding

Zhige Li,Derek Yang,Li Zhao,Jiang Bian,Tao Qin,Tie-Yan Liu

pp.894-902 (2019)

Cited by1EIBibtex

Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction

Chi Chen,Li Zhao,Jiang Bian,Chunxiao Xing,Tie-Yan Liu

pp.2376-2384 (2019)

Cited by11EIBibtex

Unified Policy Optimization for Robust Reinforcement Learning

Zichuan Lin,Li Zhao,Jiang Bian,Tao Qin,Guangwen Yang

ACML, pp.395-410, (2019)

EIBibtex

Semi-Supervised Neural Machine Translation via Marginal Distribution Estimation

Yijun Wang,Yingce Xia,Li Zhao,Jiang Bian,Tao Qin,Enhong Chen,Tie-Yan Liu

IEEE/ACM Transactions on Audio, Speech, and Language Processing, no. 10 (2019): 1564-1576

Cited by4EIWOSBibtex

Efficient Sequence Learning with Group Recurrent Networks

Fei Gao,Lijun Wu,Li Zhao,Tao Qin,Xueqi Cheng,Tie-Yan Liu

NAACL-HLT, pp.799-808, (2018)

Cited by18EIBibtex

Learning Structured Representation for Text Classification via Reinforcement Learning

Tianyang Zhang,Minlie Huang,Li Zhao

THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTI..., pp.6053-6060, (2018)

Cited by94EIBibtex

Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization

Yijun Wang,Yingce Xia,Li Zhao,Jiang Bian,Tao Qin,Guiquan Liu,Tie-Yan Liu

THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTI..., pp.5553-5560, (2018)

Cited by34EIBibtex

Word Attention for Sequence to Sequence Text Understanding

Lijun Wu,Fei Tian,Li Zhao,Jianhuang Lai,Tie-Yan Liu

THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTI..., pp.5578-5585, (2018)

Cited by14EIBibtex

Reinforcement Learning for Relation Classification From Noisy Data

Jun Feng,Minlie Huang,Li Zhao,Yang Yang,Xiaoyan Zhu

THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTI..., (2018): 5779-5786

Cited by165EIBibtex

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Li ZhaoResearch

Papers26 papers