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Refereed Conference

  1. Learning to Pre-train Graph Neural Networks.
    Y. Lu, X. Jiang, Y. Fang and C. Shi. Accepted by AAAI 2021.
    [Paper] [Code] [BibTex]

  2. Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph.
    Z. Liu, Y. Fang, C. Liu and S. C. H. Hoi. Accepted by AAAI 2021.
    [Paper] [Code] [BibTex]

  3. 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] [BibTex]

  4. 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] [BibTex]

  5. Adaptive Task Sampling for Meta-Learning.
    C. Liu*, Z. Wang*, D. Sahoo, Y. Fang, K. Zhang and S. C. H. Hoi. Accepted by ECCV 2020.
    (* Co-first authors with equal contribution.)
    [Paper] [Code] [Supplementary] [BibTex]

  6. Temporal Heterogeneous Interaction Graph Embedding For Next-Item Recommendation.
    Y. Ji, M. Yin, Y. Fang, H. Yang, X. Wang, T. Jia and C. Shi. Accepted by ECML-PKDD 2020.
    [Paper] [Code] [BibTex]

  7. Social Influence Attentive Neural Network for Friend-Enhanced Recommendation.
    Y. Lu, R. Xie, C. Shi, Y. Fang, W. Wang, X. Zhang and L. Lin. Accepted by ECML-PKDD (Applied Data Science) 2020.
    [Paper] [Code] [BibTex] [中文概述]

  8. 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]

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

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

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

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

  13. 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]

  14. 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] [Slides] [Poster] [Code] [BibTex]

  15. 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]

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

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

  18. 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]

  19. 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]

  20. 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] [Slides] [Poster] [Data & Code] [BibTex]

  21. 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] [Slides] [Data] [BibTex]

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

  23. 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] [Slides] [Poster] [Data] [BibTex]

  24. 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]

  25. 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]

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

  27. 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. Recent Advances in Network-based Methods for Disease Gene Prediction.
    S. Ata, M. Wu, Y. Fang, L. Ou-Yang, C. Kwoh and X. Li. Accepted by Briefings in Bioinformatics 2020.
    [Paper] [Code] [BibTex]

  2. 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. Accepted by TKDD 2020.
    [Paper] [Code] [BibTex]

  3. 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]

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

  5. 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]

  6. 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 TKDE 2019 (Early Access).
    [Paper] [BibTex]

  7. 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]

  8. 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]

  9. 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]

  10. 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. Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation. Abstract only.
    Y. Lu, Y. Fang, C. Shi. In SMP 2020.

  2. 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.
    [Paper] [Video] [BibTex]

  3. 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.
    (* Co-first authors with equal contribution.)
    Ranked 22/655 in the corresponding Kaggle challenge.
    [Paper] [BibTex]

  4. 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.
    [Paper] [Demo] [BibTex]

  5. 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]

  6. 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, Second Edition, 2018, pp. 211--224. Humana Press, New York, NY.


  1. Multi-View Collaborative Network Embedding. 
    S. Ata, Y. Fang, M. Wu, J. Shi, C. Kwoh, X. Li. In arXiv:2005.08189  [cs.LG].

  2. 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]


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

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