Li Zhao

Research

Machine Learning Group, Microsoft Research Asia

Show Academic Trajectory

Ego Network

D-Core

Research Interests

Author Statistics

Experience

Education

Bio

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

Papers24 papers

Sort

By YearBy Citation

RD22^2: Reward Decomposition with Representation Decomposition

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

NeurIPS 2020, (2020)

Bibtex

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)

EIBibtex

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

Independence-aware Advantage Estimation

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

(2019)

Bibtex

Demonstration Actor Critic

Guoqing Liu,Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, 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 by3EIBibtex

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

EIWOSBibtex

Trust Region Evolution Strategies

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

national conference on artificial intelligence, (2019)

Cited by8EIBibtex

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 by3EIBibtex

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 by14EIBibtex

Learning Structured Representation for Text Classification via Reinforcement Learning

Tianyang Zhang,Minlie Huang,Li Zhao

AAAI, (2018)

Cited by85EIBibtex

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

AAAI, (2018)

Cited by26EIBibtex

Word Attention for Sequence to Sequence Text Understanding

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

AAAI, (2018)

Cited by10EIBibtex

Reinforcement Learning for Relation Classification From Noisy Data

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

AAAI, (2018)

Cited by165EIBibtex

Sequence Prediction with Unlabeled Data by Reward Function Learning

Lijun Wu,Li Zhao,Tao Qin,Jianhuang Lai,Tie-Yan Liu

IJCAI, pp.3098-3104, (2017)

Cited by10EIBibtex

Attention-based LSTM for Aspect-level Sentiment Classification

Yequan Wang,Minlie Huang,Xiaoyan Zhu,Li Zhao

EMNLP, pp.606-615, (2016)

Cited by896EIBibtex

View All

Base Info Papers Patents Projects