Profile

Ph.D. Candidate, FIB-Lab, the Department of Electronic Engineering, Tsinghua University

Office: Rohm Building, Haidian District, Beijing, China, 100084

Email: gc16[at]mails[dot]tsinghua[dot]edu[dot]cn

Biography

Greetings! I am Chen Gao, a Ph.D. candidate from the Department of Electronic Engineering, Tsinghua University, supervised by Prof. Depeng Jin and Prof. Yong Li. I obtained my B.E. degree from the same department in 2016. I have been a visiting research scholar (advised by Prof. Xiangnan He and Prof. Tat-Seng Chua) in NExT++ Center at School of Computing, National University of Singapore.

My research interests include information retrieval and data mining.

Tutorial

KDD 2020, Advances in Recommender System [Website][Slides]

Selected Publications [Full List on Google Scholar]

2021

  • Learnable Embedding Sizes for Recommender Systems. S. Liu, Chen Gao, Y. Chen, D. Jin and Y. Li. (ICLR'21)

  • Group-Buying Recommendation for Social E-Commerce. J. Zhang, Chen Gao, D. Jin and Y. Li. (ICDE'21, full)

  • Disentangling User Interest and Conformity for Recommendation with Causal Embedding. Y. Zheng, Chen Gao, X. Li, X. He, D. Jin and Y. Li. (TheWebConf/WWW'21)

  • DGCN: Diversified Recommendation with Graph Convolutional Networks. Y. Zheng, Chen Gao, L. Chen, D. Jin and Y. Li. (TheWebConf/WWW'21)

2020

  • Differentially Private Local Collaborative Filtering. Chen Gao, C. Huang, D. Lin, D. Jin and Y. Li. (SIGIR'20, full)

  • Multi-behavior Recommendation with Graph Convolutional Networks. B. Jin*, Chen Gao*, X. He, D. Jin and Y. Li. (*Equal Contribution, SIGIR'20, full)

  • Item Recommendation for Word-of-Mouth Scenario in Social E-Commerce. Chen Gao, C. Huang, D. Yu, TH. Lin, H. Fu, D. Jin and Y. Li. (TKDE'20)

  • Social Recommendation with Characteristic Regularization. Chen Gao, N. Li, TH. Lin, D. Lin, J. Zhang, Y. Li and D. Jin. (TKDE'20)

  • Bundle Recommendation with Graph Convolutional Networks. J. Chang, Chen Gao, X. He, D. Jin and Y. Li.(SIGIR'20, Best Short Paper Honorable Mention Award)

  • Price-aware Recommendation with Graph Convolutional Networks. Y. Zheng, Chen Gao, X. He, Y. Li and D. Jin. (ICDE'20, full)

  • Revealing Physical World Privacy Leakage by Cyberspace Cookie Logs . H. Wang, Chen Gao, Y. Li, ZL. Zhang and D. Jin. (TNSM'20)

2019

  • Learning to Recommend with Multiple Cascading Behaviors. Chen Gao, X. He, D. Gan, X. Chen, F. Feng, Y. Li, TS. Chua and D. Jin. (TKDE'19)

  • Cross-domain Recommendation without Sharing User-relevant Data. Chen Gao, X. Chen, F. Feng, K. Zhao, X. He, Y. Li and D. Jin. (TheWebConf/WWW'19)

  • Privacy-preserving Cross-domain Location Recommendation. Chen Gao, C. Huang, Y. Yu, H. Wang, Y. Li and D. Jin. (IMWUT/UbiComp'19)

  • Neural Multi-Task Recommendation from Multi-Behavior Data. Chen Gao, X. He, D. Gan, X. Chen, F. Feng, Y. Li, TS. Chua and D. Jin. (ICDE'19, short)

  • CROSS: Cross-platform Recommendation for Online Shopping in Social Media. TH. Lin, Chen Gao and Y. Li. (SIGIR'19)

  • λOpt: Learn to Regularize Recommender Models in Finer Levels. Y. Chen, B. Chen, X. He, Chen Gao, Y. Li, JG. Lou and Y. Wang. (KDD'19)

  • DeepAPF: Deep Attentive Probabilistic Factorization for Multi-site Video Recommendation. H. Yan, X.. Chen, Chen Gao, Y. Li and D. Jin. (IJCAI'19)

  • Anonymization and De-anonymization of Mobility Trajectories: Dissecting the Gaps between Theory and Practice. H. Wang, Y. Li, Chen Gao, G. Wang, X. Tao and D. Jin. (TMC'19)

Before 2019

  • Recommender Systems with Characteristic Social Regularization. TH. Lin, Chen Gao and Y. Li. (CIKM'18, short)

  • De-anonymization of Mobility Trajectories: Dissecting the Gaps between Theory and Practice. H. Wang, Chen Gao, Y. Li, G. Wang, D. Jin and J. Sun. (NDSS'18)

  • From Fingerprint to Footprint: Revealing Physical World Privacy Leakage by Cyberspace Cookie Logs. H. Wang, Chen Gao, Y. Li, ZL. Zhang and D. Jin. (CIKM'17)

Academic Service

Senior Program Committee Member: IJCAI 2021

Program Committee Member: NeurIPS 2021, WWW 2021, AAAI 2021, ECML-PKDD 2020-2021, CIKM 2019

Invited Journal Reviewer: IEEE TKDE, IEEE TETCI