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

## Refereed Conference

Dynamic Heterogeneous Graph Embedding via Heterogeneous Hawkes Process.

Y. Ji, T. Jia,**Y. Fang**and C. Shi. Accepted by*ECML-PKDD*2021.

[Paper] [Code] [BibTex]Tail-GNN: Tail-Node Graph Neural Networks.

Z. Liu, K. Nguyen and**Y. Fang**. Accepted by*KDD*2021.

[Paper] [Code] [Slides] [Poster] [BibTex]Pre-training on Large-Scale Heterogeneous Graph.

X. Jiang, T. Jia, C. Shi,**Y. Fang**, Z. Lin and H. Wang. Accepted by*KDD*2021.

[Paper] [Code] [Slides] [Poster] [BibTex]Node-wise Localization of Graph Neural Networks.

Z. Liu,**Y. Fang**, Chenghao Liu and Steven Hoi. Accepted by*IJCAI*2021.

[Paper] [Supplementary] [Code] [Slides] [Poster] [BibTex]Meta-Inductive Node Classification across Graphs.

Z. Wen,**Y. Fang**and Z. Liu. In*SIGIR*2021, pp. 1219--1228.

[Paper] [Code] [Slides] [BibTex]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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]Basket-Sensitive Personalized Item Recommendation.

D.-T. Le, H. W. Lauw and**Y. Fang**. In*IJCAI*2017, pp. 2060--2066.

[Paper] [Slides] [Poster] [BibTex]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]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]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]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]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]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]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]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]Privacy beyond Single Sensitive Attribute.

**Y. Fang**, M. Ashrafi and S.-K. Ng. In*DEXA*2011, pp. 187--201.

[PDF] [BibTex]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

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]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. To appear in*IEEE Journal of Biomedical and Health Informatics (JBHI)*.

(* Co-corresponding authors.)

[Paper] [Supplementary] [Code] [BibTex]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]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*(Online Advance)*,*2020.

[Paper] [Code] [BibTex]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]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]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]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]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]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]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]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]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

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]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]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]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]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

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.

[Link]

## Preprint

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]