[Google Scholar] [ORCID] [ResearchGate] [Semantic Scholar]

Refereed Conference

  1. Contrastive Pre-training of GNNs on Heterogeneous Graphs.
    X. Jiang, Y. Lu, Y. Fang and C. Shi. In CIKM 2021, pp. 803--812.
    [Paper] [Code] [Slides] [BibTex]

  2. Topic-aware Heterogeneous Graph Neural Network for Link Prediction.
    S. Xu, C. Yang, C. Shi, Y. Fang, Y. Guo, T. Yang, L. Zhang and M. Hu. In CIKM 2021, pp. 2261--2270.
    [Paper] [Code] [Slides] [BibTex]

  3. Dynamic Heterogeneous Graph Embedding via Heterogeneous Hawkes Process.
    Y. Ji, T. Jia, Y. Fang and C. Shi. Accepted by ECML-PKDD 2021 Part I, pp. 388--403.
    [Paper] [Code] [Slides] [BibTex]

  4. Tail-GNN: Tail-Node Graph Neural Networks.
    Z. Liu, K. Nguyen and Y. Fang. In KDD 2021, pp. 1109--1119.
    [Paper] [Code] [Slides] [Poster] [BibTex]

  5. Pre-training on Large-Scale Heterogeneous Graph.
    X. Jiang, T. Jia, C. Shi, Y. Fang, Z. Lin and H. Wang. In KDD 2021, pp. 756--766 .
    [Paper] [Code] [Slides] [Poster] [BibTex]

  6. Node-wise Localization of Graph Neural Networks.
    Z. Liu, Y. Fang, Chenghao Liu and Steven Hoi. In IJCAI 2021, pp. 1520--1526.
    [Paper] [Supplementary] [Code] [Slides] [Poster] [BibTex]

  7. Meta-Inductive Node Classification across Graphs.
    Z. Wen, Y. Fang and Z. Liu. In SIGIR 2021, pp. 1219--1228.
    [Paper] [Code] [Slides] [BibTex]

  8. Learning to Pre-train Graph Neural Networks.
    Y. Lu, X. Jiang, Y. Fang and C. Shi. In AAAI 2021, pp. 4276--4284.
    [Paper] [Supplementary] [Code] [Slides] [Poster] [BibTex]

  9. Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph.
    Z. Liu, Y. Fang, C. Liu and S. C. H. Hoi. In AAAI 2021, pp. 4267--4275 .
    [Paper] [Supplementary] [Code] [Slides] [Poster] [BibTex]

  10. Towards Locality-Aware Meta-Learning of Tail Node Embeddings on Networks.
    Z. Liu*, W. Zhang*, Y. Fang, X. Zhang and S. C. H. Hoi. In CIKM 2020, pp. 975--984.
    (* Co-first authors with equal contribution.)
    [Paper] [Code] [Slides] [BibTex]

  11. TPR: Text-aware Preference Ranking for Recommender Systems.
    Y.-N. Chuang, C.-M. Chen, C.-J. Wang, M.-F. Tsai, Y. Fang and E. P. Lim. In CIKM 2020, pp. 215--224.
    [Paper] [Code] [Slides] [BibTex]

  12. Adaptive Task Sampling for Meta-Learning.
    C. Liu*, Z. Wang*, D. Sahoo, Y. Fang, K. Zhang and S. C. H. Hoi. In ECCV 2020 Part XVIII, pp 752--769.
    (* Co-first authors with equal contribution.)
    [Paper] [Supplementary] [Code] [Slides] [BibTex]

  13. Temporal Heterogeneous Interaction Graph Embedding For Next-Item Recommendation.
    Y. Ji, M. Yin, Y. Fang, H. Yang, X. Wang, T. Jia and C. Shi. In ECML-PKDD 2020 Part III, pp. 314--329.
    [Paper] [Code] [Slides] [BibTex]

  14. Social Influence Attentive Neural Network for Friend-Enhanced Recommendation.
    Y. Lu, R. Xie, C. Shi, Y. Fang, W. Wang, X. Zhang and L. Lin. In ECML-PKDD 2020 Part IV (Applied Data Science), pp. 3--18.
    [Paper] [Code] [Slides] [BibTex] [中文概述]

  15. Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation.
    Y. Lu, Y. Fang and C. Shi. In KDD 2020, pp. 1563--1573.
    [Paper] [Code] [Slides] [Video] [Poster] [BibTex] [中文概述]

  16. BiANE: Bipartite Attributed Network Embedding.
    W. Huang, Y. Li, Y. Fang, J. Fan and H. Yang. In SIGIR 2020, pp. 149--158.
    [Paper] [Code] [Slides] [BibTex] [中文概述]

  17. Multiplex Memory Network for Collaborative Filtering.
    X. Jiang, B. Hu, Y. Fang and C. Shi. In SDM 2020, pp. 91--99.
    [Paper] [Supplementary] [Code] [BibTex] [中文概述]

  18. Correlation-Sensitive Next-Basket Recommendation.
    D.-T. Le, H. W. Lauw and Y. Fang. In IJCAI 2019, pp. 2808--2814.
    [Paper] [Code] [Slides] [Poster] [BibTex]

  19. Adversarial Learning on Heterogeneous Information Networks.
    B. Hu, Y. Fang and C. Shi. In KDD 2019, pp. 120--129.
    [Paper] [Code] [Poster] [BibTex] [中文概述]

  20. Heterogeneous Embedding Propagation for Large-scale E-Commerce User Alignment.
    V. W. Zheng, M. Sha, Y. Li, H. Yang, Y. Fang, Z. Zhang, K.-L. Tan and K. C.-C. Chang. In ICDM 2018 (Short), pp. 1434--1439.
    [Paper] [Slides] [Poster] [BibTex]

  21. Modeling Contemporaneous Basket Sequences with Twin Networks for Next-Item Recommendation.
    D.-T. Le, H. W. Lauw and Y. Fang. In IJCAI 2018, pp. 3414--3420.
    [Paper] [Code] [Slides] [Poster] [BibTex]

  22. Region Average Pooling for Context-Aware Object Detection.
    K. Kuan, G. Manek, J. Lin, Y. Fang and V. Chandrasekhar. In ICIP 2017, pp. 1347--1351.
    [Paper] [BibTex]

  23. Object Detection Meets Knowledge Graphs.
    Y. Fang, K. Kuan, J. Lin, C. Tan and V. Chandrasekhar. In IJCAI 2017, pp. 1661--1667.
    [Paper] [Code] [Slides] [Poster] [BibTex]

  24. Basket-Sensitive Personalized Item Recommendation.
    D.-T. Le, H. W. Lauw and Y. Fang. In IJCAI 2017, pp. 2060--2066.
    [Paper] [Slides] [Poster] [BibTex]

  25. Modeling Sequential Preferences with Dynamic User and Context Factors.
    D.-T. Le, Y. Fang and H. W. Lauw. In ECML-PKDD 2016, pp. 145--161.
    [Paper] [Supplementary] [Slides] [Poster] [BibTex]

  26. Learning to Query: Focused Web Page Harvesting for Entity Aspects.
    Y. Fang, V. W. Zheng and K. C.-C. Chang. In ICDE 2016, pp. 1002--1013.
    [Paper] [Slides] [Poster] [BibTex]

  27. Semantic Proximity Search on Graphs with Metagraph-based Learning.
    Y. Fang, W. Lin, V. W. Zheng, M. Wu, K. C.-C. Chang and X. Li. In ICDE 2016, pp. 277--288.
    [Paper] [Code] [Slides] [Poster] [BibTex]

  28. Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically.
    Y. Fang, K. C.-C. Chang and H. W. Lauw. In ICML 2014 (2), pp. 406--414.
    [Paper] [Supplementary] [Data] [Slides] [BibTex]

  29. Incremental and Accuracy-Aware Personalized PageRank through Scheduled Approximation.
    F. Zhu, Y. Fang, K. C.-C. Chang and J. Ying. In VLDB 2013, 6(6), pp. 481--492.
    Extended version invited to the collection of Best Papers of VLDB'13.
    [Paper] [Data] [Slides] [BibTex]

  30. RoundTripRank: Graph-based Proximity with Importance and Specificity.
    Y. Fang, K. C.-C. Chang and H. W. Lauw. In ICDE 2013, pp. 613--624.
    [Paper] [Data] [Slides] [Poster] [BibTex]

  31. Confidence-Aware Graph Regularization with Heterogeneous Pairwise Features.
    Y. Fang, P. Hsu and K. C.-C. Chang. In SIGIR 2012, pp. 951--960.
    [Paper] [Slides] [BibTex]

  32. Searching Patterns for Relation Extraction over the Web: Rediscovering the Pattern-Relation Duality.
    Y. Fang and K. C.-C. Chang. In WSDM 2011, pp. 825--834.
    [Paper] [Poster] [BibTex]

  33. Privacy beyond Single Sensitive Attribute.
    Y. Fang, M. Ashrafi and S.-K. Ng. In DEXA 2011, pp. 187--201.
    [PDF] [BibTex]

  34. Efficient Skyline Maintenance for Streaming Data with Partially-Ordered Domains.
    Y. Fang and C. Y. Chan. In DASFAA 2010, pp. 322--336.
    [Paper] [Slides] [BibTex]

Refereed Journal

  1. Unified and Incremental SimRank: Index-free Approximation with Scheduled Principle.
    F. Zhu, Y. Fang, K. Zhang, Z. Jiang, M. Wu, H. Cao and K. C.-C. Chang. To appear in IEEE TKDE.
    Paper] [Code] [BibTex]

  2. Neighbor-Anchoring Adversarial Graph Neural Networks.
    Z. Liu, Y. Fang*, Y. Liu, V. W. Zheng. To appear in IEEE TKDE.
    (* Corresponding author.)
    [Paper] [Code] [BibTex]

  3. Prediction of Synthetic Lethal Interactions in Human Cancers using Multi-view Graph Auto-Encoder.
    Z. Hao, D. Wu, Y. Fang*, M. Wu*, R. Cai* and Xiao-Li Li. In IEEE J. of Biomedical & Health Informatics (JBHI) 25(10), 2021, pp. 4041--4051.
    (* Co-corresponding authors.)
    [Paper] [Supplementary] [Code] [BibTex]

  4. Multi-View Collaborative Network Embedding.
    S. Ata, Y. Fang*, M. Wu*, J. Shi, C. Kwoh, X. Li. In ACM TKDD 15(3), Article No. 39, 2021.
    (* Co-corresponding authors.)
    [Paper] [Code] [BibTex]

  5. Recent Advances in Network-based Methods for Disease Gene Prediction.
    S. Ata, M. Wu, Y. Fang, L. Ou-Yang, C. Kwoh and X. Li. In Briefings in Bioinformatics 22(4), Article No. bbaa303, 2020.
    [Paper] [Code] [BibTex]

  6. Accelerating Large-Scale Heterogeneous Interaction Graph Embedding Learning via Importance Sampling.
    Y. Ji, M. Yin, H. Yang, J. Zhou, V. W. Zheng, C. Shi* and Y. Fang*. In ACM TKDD 15(1), Article No.10, 2020.
    (* Co-corresponding authors.)
    [Paper] [Code] [BibTex]

  7. Semi-supervised Co-Clustering on Attributed Heterogeneous Information Networks.
    Y. Ji, C. Shi, Y. Fang, X. Kong and M. Yin. In IPM 57(6), 2020.
    [Paper] [Code] [BibTex]

  8. mg2vec: Learning Relationship-Preserving Heterogeneous Graph Representations via Metagraph Embedding.
    W. Zhang, Y. Fang*, Z. Liu, M. Wu and X. Zhang*. In IEEE TKDE (Early Access), 2020.
    (* Co-corresponding authors.)
    [Paper] [Code] [BibTex]

  9. Dual-Dropout Graph Convolutional Network for Predicting Synthetic Lethality in Human Cancers.
    R. Cai, X. Chen, Y. Fang*, M. Wu* and Y. Hao. In Bioinformatics 36(16), 2020, pp. 4458--4465.
    (* Co-corresponding authors.)
    [Paper] [Code] [Supplementary] [BibTex]

  10. Metagraph-based Learning on Heterogeneous Graphs.
    Y. Fang, W. Lin, V. W. Zheng, M. Wu, J. Shi, K. C.-C. Chang and X. Li. In IEEE TKDE 33(1), 2019, pp. 154--168.
    [Paper] [Code] [BibTex]

  11. Integrating Node Embeddings and Biological Annotations for Genes to Predict Disease-Gene Associations.
    S. Ata, L. Ou-Yang, Y. Fang, C.-K. Kwoh, M. Wu and X. Li. In BMC Systems Biology 12(Supp 9), 2018, pp. 31--44.
    Invited for oral presentation at GIW'18.
    [Paper] [BibTex]

  12. Disease Gene Classification with Metagraph Representations.
    S. Ata, Y. Fang, M. Wu, X. Xiao and X. Li. In Methods 131, 2017, pp. 83--92.
    [Paper] [BibTex]

  13. Scheduled Approximation for Personalized PageRank with Utility-Driven Hub Selection.
    F. Zhu, Y. Fang, K. C.-C. Chang and J. Ying. In VLDBJ 24(5), 2015, Special Issue on Best Papers of VLDB'13, pp. 655--679.
    [Paper] [Data] [BibTex]

  14. Entity Linking on Microblogs with Spatial and Temporal Signals.
    Y. Fang and M.-W. Chang. In TACL 2(Oct), 2014, pp. 259--272.
    Invited for oral presentation at EMNLP'14.
    [Paper] [Slides] [Data] [BibTex]

Refereed Workshop/Demo/Abstract

  1. Network Embedding with Attribute Refinement. [Workshop paper]
    T. Xiao, Y. Fang, H. Yang and V. W. Zheng. In KDD Workshop on Mining and Learning with Graphs 2017 (non-archival).
    [Paper] [Video] [BibTex]

  2. Truly Multi-modal YouTube-8M Video Classification with Video, Audio, and Text. [Workshop paper]
    Z. Wang*, K. Kuan*, M. Ravaut*, G. Manek*, S. Song*, Y. Fang, et al. In CVPR Workshop on YouTube-8M Challenge 2017 (non-archival).
    (* Co-first authors with equal contribution.)
    Ranked 22/655 in the corresponding Kaggle challenge.
    [Paper] [BibTex]

  3. ARISE-PIE: A People Information Integration Engine over the Web. [Workshop paper]
    V. W. Zheng, T. Hoang, P. Chen, Y. Fang, X. Yang and K. C.-C. Chang. In CIKM Workshop on Data-Driven Talent Acquisition 2016 (non-archival).
    [Paper] [Demo] [BibTex]

  4. IntelligShop: Enabling Intelligent Shopping in Malls through Location-based Augmented Reality. [Demo paper]
    A. Adhikari, V. W. Zheng, H. Cao, M. Lin, Y. Fang and K. C.-C. Chang. In ICDM 2015, pp. (W)1604--1607.
    Featured in media coverage in the United States.
    [Paper] [Demo] [News] [BibTex]

  5. Differences in Plasma Lipids during Rested Wakefulness and Sleep Deprivation. [Abstract only]
    S. Huang, E. C.-P. Chua, G. Shui, Y. Fang, S.-C. Yeo, M. R. Wenk and J. J. Gooley. In SLEEP 2015.
    [Abstract] [Poster]

Book Chapter

  1. Disease Gene Classification with Metagraph Representations.
    S. Ata, Y. Fang, M. Wu, X. Li and X. Xiao. In H. Mamitsuka (Ed.) Data Mining for Systems Biology: Methods and Protocols, 2nd Edition, 2018, pp. 211--224. Humana Press, New York, NY.


  1. End-to-End Video Classification with Knowledge Graphs.
    Y. Fang, Zhe Wang, Jie Lin, Luis Fernando D’Haro, Kim Jung Jae, Zeng Zeng and Vijay Chandrasekhar. In arXiv:1711.01714 [cs.CV].
    [PDF] [BibTex]


  1. Walking Forward and Backward: Towards Graph-based Searching and Mining.
    Y. Fang. PhD Dissertation, University of Illinois at Urbana-Champaign, 2014.

  2. Finding Skyline Objects in Streaming Data.
    Y. Fang. Honors Year Dissertation, National University of Singapore, 2009.