My publications can also be found at Google Scholar and ORCID.

Refereed Conference

1. 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]
   
   
2. Adversarial Learning on Heterogeneous Information Networks.
   B. Hu, Y. Fang and C. Shi. In KDD 2019, pp. 120--129.
   [Paper] [Poster] [Data & Code] [BibTex]
   
   
3. 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, pp. 1434--1439.
   [Paper] [Slides] [Poster] [BibTex]
   
   
4. 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]
   
   
5. 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]
   
   
6. 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] [BibTex]
   
   
7. Basket-Sensitive Personalized Item Recommendation.
   D.-T. Le,  H. W. Lauw and Y. Fang. In IJCAI 2017, pp. 2060--2066.
   [Paper] [Slides] [Poster] [BibTex]
   
   
8. 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]
   
   
9. 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]
   
   
10. 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]
    
    
11. 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]
    
    
12. 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]
    
    
13. 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]
    
    
14. 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]
    
    
15. 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]
    
    
16. Privacy beyond Single Sensitive Attribute.
    Y. Fang, M. Ashrafi and S.-K. Ng. In DEXA 2011, pp. 187--201.
    [PDF] [BibTex]
    
    
17. 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. 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]
   
   
2. Integrating Node Embeddings and Biological Annotations for Genes to Predict Disease-Gene Associations.
   S. Kircali, L. Ou-Yang, Y. Fang, C.-K. Kwoh, M. Wu and X. Li. In BMC Systems Biology 2018, Vol. 12(Supp 9), pp. 31--44.
   Invited for oral presentation at GIW'18.
   [Paper] [BibTex]
   
   
3. Disease Gene Classification with Metagraph Representations.
   S. Kircali, Y. Fang, M. Wu, X. Xiao and X. Li. In Methods 131, 2017, pp. 83--92.
   [Paper] [BibTex]
   
   
4. 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]
   
   
5. 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. 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 2017.
   Ranked 22/655 in the corresponding Kaggle challenge.
   [Paper] [BibTex]
   
   
2. 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 2016.
   [Paper] [Demo] [BibTex]
   
   
3. 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]
   
   
4. 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 38(Abstract), 2015, pp. A110.
   [Abstract] [Poster]
   
   

Book Chapter

1. Disease Gene Classification with Metagraph Representations.
   S. Kircali, 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.
   [Link]

Preprint

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]

Dissertation

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]