Refereed Conference
- Learning
to Pre-train Graph Neural Networks.
Y. Lu, X. Jiang, Y. Fang and C. Shi. Accepted by AAAI 2021. [Paper] [Supplementary] [Code] [BibTex]
- 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] [Supplementary] [Code] [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] [Code] [Slides] [Supplementary] [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. Accepted by ECML-PKDD 2020.
[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. Accepted by ECML-PKDD (Applied Data Science) 2020.
[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] [Code] [Supplementary] [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] [Slides] [Poster] [Code] [BibTex]
- 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]
- 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] [Slides] [Poster] [Code] [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] [Slides] [Poster] [Code] [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]
[Slides]
[Poster]
[Code]
[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]
[Slides]
[Data]
[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] [Slides] [Data] [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]
[Slides]
[Poster]
[Data]
[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
- Multi-View Collaborative Network Embedding.
S. Ata, Y. Fang*, M. Wu*, J. Shi, C. Kwoh, X. Li. Accepted by TKDD. (* 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] [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 TKDD 15(1), 2020.
[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 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 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
- Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation. Abstract only.
Y. Lu, Y. Fang, C. Shi. In SMP 2020.
[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.
[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.
(* 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.
[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, Second 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]
Dissertation
- Walking Forward and Backward: Towards Graph-based Searching and Mining.
Y. Fang. PhD Dissertation, University of Illinois at Urbana-Champaign, 2014.
[PDF]
- Finding Skyline Objects in Streaming Data.
Y. Fang. Honors Year Dissertation, National University of Singapore, 2009. [PDF]
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