News


16 May 2020
Two full papers are accepted by KDD, on conversational recsys and enterprise competition analysis.

24 April 2020
One tutorial about conversational recsys is accepted by SIGIR!.

23 April 2020
Two full papers from my USTC group are accepted by SIGIR, on GCN and meta-learning for recsys. Congrats to all!

20 April 2020
One paper is accepted by IJCAI about enhancing GCN with neighbor interactions.

9 April 2020
I serve as Editorial Board member of the AI Open journal. Welcome to submit!

11 Jan 2020
Two papers are accepted by WWW about knowledge graph-enhanced negative sampling and sequential recommendation.

28 Nov 2019
Two papers are accepted by TKDE about adversarial training on graph and multi-behavior recommendation.

11 Nov 2019
Two papers are accepted by AAAI 2020 about robust network embedding and unfollow prediction in social network.

11 Oct 2019
One paper is accepted by WSDM 2020 about conversational recommender system.

2 Oct 2019
Two papers are accepted by ICDE 2020 about price-aware recommendation recommendation, and neural relation extraction.

28 July 2019
Two papers are accepted by TKDE about group recommendation, and negative sampler with view data.

26 July 2019
One paper is accepted by TMM about multi-modal social event analysis, and one paper is accepted by ICCV 2019 (oral) about scene graph generation.

26 July 2019
One paper is accepted by TOIS on extending convolutional neural collaborative filtering.

11 May 2019
Three full papers are accepted by ACM Multimedia 2019, on micro-video recommendation, mix-dish recognition, and image subjective attributes.

30 April 2019
Four papers are accepted by KDD 2019 research track, about knowledge graph for recommendation, learning to regularize, sequential set prediction, and time series prediction, respectively.

14 April 2019
Three full papers are accepted by SIGIR 2019, about graph neural network for recommendation, knowledge-based recommendation and interpretable fashion matching, respectively.

23 Feb 2019
I am invited to be an area chair of the ACM Multimedia 2019 conference, of the multimedia search and recommendation track.

21 Jan 2019
Two papers are accepted by WWW 2019, about privacy-preserving cross-domain recommendation and knowledge graph based recommendation.

19 Jan 2019
Two papers are accepted by TOIS, about stock prediction and review-aware recommendation.

1 Jan 2019
One paper is accepted by TNNLS which explores the weights of missing data for matrix factorization.

1 Nov 2018
Two papers are accepted by AAAI 2019. One performs knowledge graph reasoning for explainable recommendation, one explores self-attention for Video QA.

22 Oct 2018
One paper about session-based recommendation is accepted by WSDM 2019.

27 Sep 2018
One paper about using multiple types of user behaviors for recommendation is accepted by ICDE 2019.

2 July 2018
Three full papers are accepted by MM 2018. One paper about multimodal dialog systems is in the Best Paper Final List.

16 May 2018
One full paper is accepted by UAI 2018.

27 April 2018
Two awards from WWW 2018! One short paper receives Best Poster Award, and one long paper receives Best Paper Award Honorable Mention.

23 April 2018
Two papers are accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE)!


22 April 2018
Call for papers: MMSJ Special Issue on Multimedia Recommendation.

21 April 2018
Two full research papers are accepted by ACL 2018!

17 April 2018
Five full research papers are accepted by IJCAI 2018!

12 April 2018
Six full research papers are accepted by SIGIR 2018!

5 March 2018
Two tutorials are accepted by SIGIR 2018!

5 March 2018
I am invited to be a program committee member in MM 2018 and CIKM 2018.

25 Feb 2018
One poster paper advised by me is accepted by WWW 2018, about negative sampler for BPR.

28 Dec 2017
I am invited to be a program committee member in KDD 2018 and SIGIR 2018.

23 Dec 2017
One full paper about entity resolution is accepted by ICDE 2018.

22 Dec 2017
Three full papers advised by me are accepted by WWW 2018! About tree+embedding for explainable recommendation, aesthetic-aware clothing recommendation, and hypergraph learning.

4 Dec 2017
Our tutorial proposal on "Deep Learning for Matching in Search and Recommendation" is accepted by WWW 2018.

3 Dec 2017
I am invited to be a program committee member in ACL 2018 and PAKDD 2018.


13 Nov 2017
I am invited to be a program committee member in IJCAI 2018.


Xiangnan HE 

Professor

School of Data Science
School of Information Science and Technology
University of Science and Technology of China

443 Huangshan Road, Hefei, China 230027

Email: xiangnanhe at gmail.com

I lead the USTC Lab for Data Science. My research interests span information retrieval, data mining, and multi-media analytics. I have over 70 publications appeared in several top conferences such as SIGIR, WWW, KDD, and MM, and journals including TKDE, TOIS, and TMM. My work on recommender systems has received the Best Paper Award Honourable Mention in WWW 2018 and ACM SIGIR 2016. Moreover, I have served as the (senior) PC member for several top conferences including SIGIR, WWW, KDD, MM etc., and the regular reviewer for journals including TKDE, TOIS, TMM, etc.

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2. Hiring PhD and MSc students. Requirements:
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3. IJCIS Special Issue Call for Papers:
- Topic: Adversarial Attack and Defense for Intelligence Systems
- Submission Deadline: 30 July 2020

Tutorials


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Conversational Recommendation: Formulation, Methods, and Evaluation
Wenqiang Lei, Xiangnan He, Maarten de Rijke & Tat-Seng Chua
SIGIR 2020,    Slides

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Learning and Reasoning on Graph for Recommendation
Xiang Wang, Xiangnan He, & Tat-Seng Chua
CIKM 2019,    WSDM 2020 Slides

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Deep Learning for Matching in Search and Recommendation
Jun Xu, Xiangnan He, & Hang Li
SIGIR 2018,    WWW 2018,    WSDM 2019 Slides

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Information Discovery in E-commerce
Zhaochun Ren, Xiangnan He, Dawei Yin, & Maarten de Rijke
SIGIR 2018    Slides (2018/7/8 @ Ann Arbor Michigan, US)   

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Recommendation Technologies for Multimedia Content
Xiangnan He, Hanwang Zhang & Tat-Seng Chua
ICMR 2018    Slides (2018/6/11 @ Yokohama, Japan)   

Selected Publications

(Full list see my [Group Homepage] [Google Scholar] )
In the Year of 2020:


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LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang and Meng Wang
SIGIR 2020 (Full, Accept rate: 26%)    Codes

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How to Retrain Recommender System? A Sequential Meta-Learning Approach
Yang Zhang, Fuli Feng, Chenxu Wang, Xiangnan He, Meng Wang, Yan Li and Yongdong Zhang
SIGIR 2020 (Full, Accept rate: 26%)    Codes

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Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation
Fajie Yuan, Xiangnan He, Alexandros Karatzoglou and Liguang Zhang
SIGIR 2020 (Full, Accept rate: 26%)    Codes

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Interactive Path Reasoning on Graph for Conversational Recommendation
Wenqiang Lei, Gangyi Zhang, Xiangnan He*, Yisong Miao, Xiang Wang, Liang Chen and Tat-Seng Chua
KDD 2020 (Full, Accept rate: 16.9%)    Corresponding author

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Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems
Wenqiang Lei, Xiangnan He*, Yisong Miao, Qingyun Wu, Richang Hong, Min-Yen Kan & Tat-Seng Chua
WSDM 2020 (Full, Accept rate: 15%)    Slides    Data & Codes *Corresponding author

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Reinforced Negative Sampling over Knowledge Graph for Recommendation
Xiang Wang, Yaokun Xu, Xiangnan He, Yixin Cao, Weng Wang & Tat-Seng Chua
WWW 2020 (Full, Accept rate: 19%)    Codes

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Future Data Helps Training: Modelling Future Contexts for Session-based Recommendation
Fajie Yuan, Xiangnan He, Haochuan Jiang, Guibing Guo, Jian Xiong, Zhezhao Xu & Xiong Yilin
WWW 2020 (Full, Accept rate: 19%)    Codes    Slides

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Bilinear Graph Neural Network with Neighbor Interactions
Hongmin Zhu, Fuli Feng, Xiangnan He, Xiang Wang, Yan Li, Kai Zheng & Yongdong Zhang
IJCAI 2020 (Full, Accept rate: 12.6%)    Codes

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Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning
Daizong Ding, Mi Zhang, Xudong Pan, Min Yang & Xiangnan He
AAAI 2020 (Full, Accept rate: 20.6%)   

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Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure
Fuli Feng, Xiangnan He*, Jie Tang & Tat-Seng Chua
IEEE Transactions on Knowledge and Data Engineering (TKDE 2020)    Codes *Corresponding author
In the Year of 2019:


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Neural Graph Collaborative Filtering
Xiang Wang, Xiangnan He*, Meng Wang, Fuli Feng & Tat-Seng Chua
SIGIR 2019 (Full, Accept rate: 20%)    Slides   Codes *Corresponding author

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Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation
Xin Xin, Xiangnan He*, Yongfeng Zhang, Yongdong Zhang & Joemon Jose
SIGIR 2019 (Full, Accept rate: 20%)    Slides    Codes *Corresponding author

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KGAT: Knowledge Graph Attention Network for Recommendation
Xiang Wang, Xiangnan He*, Yixin Cao, Meng Liu & Tat-Seng Chua
KDD 2019 (Full, Accept rate: 14.2%)    Codes    Poster*Corresponding author

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λOpt: Learn to Regularize Recommender Models in Finer Levels
Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou & Yue Wang
KDD 2019 (Full Oral, Accept rate: 9.2%)    Codes    Slides    Poster   

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Modeling Extreme Events in Time Series Prediction
Daizong Ding, Mi Zhang, Xudong Pan, Min Yang & Xiangnan He
KDD 2019 (Full Oral, Accept rate: 9.2%)    Slides    Poster   

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Semi-supervised User Profiling with Heterogeneous Graph Attention Networks
Weijian Chen, Yulong Gu, Zhaochun Ren*, Xiangnan He*, Hongtao Xie, Tong Guo, Dawei Yin & Yongdong Zhang
IJCAI 2019 (Full, Accept rate: 17.9%)    Codes    Slides    *Corresponding author

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Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preference
Yixin Cao, Xiang Wang, Xiangnan He*, Zikun Hu & Tat-Seng Chua
WWW 2019 (Full, Accept rate: 18%)    Codes *Corresponding author

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Explainable Reasoning over Knowledge Graph Paths for Recommendation
Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao & Tat-Seng Chua
AAAI 2019 (Full, Accept rate: 16.2%)    Codes    Slides

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A Simple Convolutional Generative Network for Next-item Recommendation
Fajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose & Xiangnan He
WSDM 2019 (Full, Accept rate: 16.4%)    Codes   

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Fast Matrix Factorization with Non-Uniform Weights on Missing Data
Xiangnan He, Jinhui Tang, Xiaoyu Du, Richang Hong, Tongwei Ren & Tat-Seng Chua
IEEE Transactions on Neural Networks and Learning Systems (TNNLS 2019, IF=7.982)    Codes   
In the Year of 2018:


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Adversarial Personalized Ranking for Recommendation
Xiangnan He, Zhankui He, Xiaoyu Du & Tat-Seng Chua
SIGIR 2018 (Full, Accept rate: 21%)    Codes   Slides   

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Knowledge-aware Multimodal Dialog Systems
Lizi Liao, Yunshan Ma, Xiangnan He, Richang Hong & Tat-Seng Chua
MM 2018 (Full, oral, Accept rate: 8.5%)    Slides   (Best Paper Final List)

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Aesthetic-based Clothing Recommendation
Wenhui Yu, Huidi Zhang, Xiangnan He, Xu Chen, Li Xiong & Zheng Qin
WWW 2018 (Accept rate: 14.8%)    Slides   Codes   (Best Paper Award Honorable Mention)

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TEM: Tree-enhanced Embedding Model for Explainable Recommendation
Xiang Wang, Xiangnan He*, Fuli Feng, Liqiang Nie & Tat-Seng Chua
WWW 2018 (Accept rate: 14.8%)    Codes are under request.    Slides   *Corresponding author.

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Learning on Partial-Order Hypergraphs
Fuli Feng, Xiangnan He*, Yiqun Liu, Liqiang Nie & Tat-Seng Chua
WWW 2018 (Accept rate: 14.8%)    Codes are under request.    Slides   *Corresponding author.

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An Improved Sampler for Bayesian Personalized Ranking by Leveraging View Data
Jingtao Ding, Fuli Feng, Xiangnan He, Guanghui Yu, Yong Li & Depeng Jin
WWW 2018 (Poster)    Codes    (Best Poster Award)

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Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures
Wenqiang Lei, Xisen Jin, Min-Yen Kan, Zhaochun Ren, Xiangnan He & Dawei Yin.
ACL 2018 (Full)    Codes    Slides

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Attributed Social Network Embedding
Lizi Liao, Xiangnan He*, Hanwang Zhang, & Tat-Seng Chua
IEEE Transactions on Knowledge and Data Engineering (TKDE)    Codes    *Corresponding author

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NAIS: Neural Attentive Item Similarity Model for Recommendation
Xiangnan He, Zhankui He, Jingkuan Song, Zhenguang Liu, Yu-Gang Jiang, & Tat-Seng Chua
IEEE Transactions on Knowledge and Data Engineering (TKDE)    Codes
In the Year of 2017:


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Neural Factorization Machines for Sparse Predictive Analytics
Xiangnan He & Tat-Seng Chua
SIGIR 2017 (Accept rate: 22%)    Codes    Slides   

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Item Silk Road: Recommending Items from Information Domains to Social Users
Xiang Wang, Xiangnan He*, Liqiang Nie & Tat-Seng Chua
SIGIR 2017 (Accept rate: 22%)    Codes    Slides    *Corresponding author

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Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-level Attention
Jingyuan Chen, Hanwang Zhang, Xiangnan He*, Liqiang Nie, Wei Liu & Tat-Seng Chua
SIGIR 2017 (Accept rate: 22%)    Codes    Slides    *Corresponding author

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Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
Jun Xiao, Hao Ye, Xiangnan He*, Hanwang Zhang, Fei Wu & Tat-Seng Chua
IJCAI 2017 (Accept rate: 26%)    Codes    Slides    *Corresponding author

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Neural Collaborative Filtering
Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu & Tat-Seng Chua
WWW 2017 (Accept rate: 17%)    Codes    Slides

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A Generic Coordinate Descent Framework for Learning from Implicit Feedback
Immanuel Bayer*, Xiangnan He*, Bhargav Kanagal & Steffen Rendle
WWW 2017 (Accept rate: 17%)    *Joint work at Google.

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BiRank: Towards Ranking on Bipartite Graphs
Xiangnan He, Ming Gao, Min-Yen Kan & Dingxian Wang
IEEE Transactions on Knowledge and Data Engineering (TKDE)   
Before 2017:


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Fast Matrix Factorization for Online Recommendation with Implicit Feedback
Xiangnan He, Hanwang Zhang, Min-Yen Kan & Tat-Seng Chua
SIGIR 2016.   (Accept rate: 18%)    Codes    Slides

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Discrete Collaborative Filtering
Hanwang Zhang, Fumin Shen, Wei Liu, Xiangnan He, Huanbo Luan & Chua Tat-Seng
SIGIR 2016.   (Accept rate: 18%)    Codes    Slides (Best Paper Award Honorable Mention)

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Context-aware Image Tweets Modelling and Recommendation
Tao Chen, Xiangnan He & Min-Yen Kan
MM 2016.   (Accept rate: 20%)    Codes

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TriRank: Review-aware Explainable Recommendation by Modeling Aspects
Xiangnan He, Tao Chen, Min-Yen Kan & Xiao Chen
CIKM 2015.   (Accept rate: 18%)    Slides

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Relating an Image Tweet’s Text and Images
Tao Chen, Hany M. SalahEldeen, Xiangnan He, Min-Yen Kan & Dongyuan Lu
AAAI 2015.   (Accept rate: 26.7%)    Codes

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Predicting the Popularity of Web 2.0 Items Based on User Comments
Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu & Kazunari Sugiyama
SIGIR 2014.   (Accept rate: 21%)   Slides

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Comment-based Multi-View Clustering of Web 2.0 Items
Xiangnan He, Min-Yen Kan, Peichu Xie & Xiao Chen
WWW 2014.   (Accept rate: 12.9%) Supplement  Slides  Codes

Professional Services

Journal Editorial Board:
AI Open --- A new AI journal for open and sharing
Conference/Workshop Organization:
Doctoral Consortium Chair of WSDM 2020
Area Chair (Multimedia Search and Recommendation) of ACM Multimedia 2020
Applied Data Science Chair of ECML-PKDD 2020
Workshop Co-Chair of the SIGIR 2020 Workshop on Information Retrieval in Finance (FinIR)
Area Chair (NLP Applications) of CCF NLPCC 2020
Special Session Chair of ACM Multimedia Asia 2020
Youth Forum Chair of China Conference on Information Retrieval (CCIR 2020)
Program Chair of IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS 2019)
Area Chair (Multimedia Search and Recommendation) of ACM Multimedia 2019
Workshop Co-Chair of the CIKM 2017 Workshop on Social Media Analytics for Smart Cities
PC/SPC Member of Conferences:
2020: SIGIR, WWW, KDD, NeuIPS, WSDM, CIKM, AAAI, IJCAI, EMNLP, ICTIR
2019: SIGIR, WWW, KDD, WSDM, CIKM, AAAI, IJCAI, ACL, ICME
2018: SIGIR, WWW, KDD, WSDM, CIKM, AAAI, IJCAI, EMNLP, ACL, MM, AIRS, PAKDD
2017: SIGIR, WWW, CIKM, MM
2016: SIGIR, WWW, EMNLP

Experiences

Professor, University of Science and Technology of China, April 2019 - Present
Postdoc Research Fellow, National University of Singapore, May 2016 - March 2019
Advisior: Chua Tat-Seng (NExT: NUS-Tsinghua Extreme Search Center)
Research Intern, Google Research (Mountain View), June 2015 - Sep 2015
Advisior: Bhargav Kanagal and Steffen Rendle (Strategic Technology Group)
Software Engineering Intern, Google (New York), June 2014 - Sep 2014
Advisior: Thomas Sidoti and Sheng Zhang (Local Search Group)
Software Engineering Intern, Microsoft (Shanghai), Sep 2010 - Dec 2010
Advisior: Leon Chen (Operating System Group)

Education

National University of Singapore (NUS)
Ph.D. in Computer Science                   July 2011 - April 2016, Singapore
Advisor: Prof. Kan Min-Yen
East China Normal University (ECNU)
Bachelor in Software Engineering      Sep 2007 - June 2011, Shanghai
Advisor: Prof. Jin Cheqing and Prof. Zhou Aoying

Useful Links

NUS CS Conference Rankings
NUS CS Journal Ranking
NUS CS Courses
Machine Learning Reading List
Deep Learning Reading List

Last update: May 31, 2020. Webpage template borrows from Weinan Zhang.