Yuan Fang

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 88

Top Topics

Preference Learning

Item Recommendation

Graph Representations

Top Venues

IEEE Trans. Knowl. Data Eng.

Publications

Xingtong Yu, Yuan Fang, Zemin Liu, Yuxia Wu, Zhihao Wen, Jianyuan Bo, Xinming Zhang, Steven C. H. Hoi
Few-Shot Learning on Graphs: from Meta-learning to Pre-training and Prompting. CoRR (2024)
Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhang
Text-Free Multi-domain Graph Pre-training: Toward Graph Foundation Models. CoRR (2024)
Zhihao Wen, Jie Zhang, Yuan Fang
SIBO: A Simple Booster for Parameter-Efficient Fine-Tuning. CoRR (2024)
Jianyuan Bo, Yuan Fang
Contrastive General Graph Matching with Adaptive Augmentation Sampling. CoRR (2024)
Trung-Kien Nguyen, Yuan Fang
Diffusion-based Negative Sampling on Graphs for Link Prediction. CoRR (2024)
Zemin Liu, Yuan Fang, Wentao Zhang, Xinming Zhang, Steven C. H. Hoi
Locality-Aware Tail Node Embeddings on Homogeneous and Heterogeneous Networks. IEEE Trans. Knowl. Data Eng. 36 (6) (2024)
Zhihao Wen, Yuan Fang, Pengcheng Wei, Fayao Liu, Zhenghua Chen, Min Wu
Temporal and Heterogeneous Graph Neural Network for Remaining Useful Life Prediction. CoRR (2024)
Chuan Shi, Cheng Yang, Yuan Fang, Lichao Sun, Philip S. Yu
Lecture-style Tutorial: Towards Graph Foundation Models. WWW (Companion Volume) (2024)
Yuxia Wu, Yuan Fang, Lizi Liao
On the Feasibility of Simple Transformer for Dynamic Graph Modeling. WWW (2024)
Trung-Kien Nguyen, Yuan Fang
Diffusion-based Negative Sampling on Graphs for Link Prediction. WWW (2024)
Xingtong Yu, Yuan Fang, Zemin Liu, Xinming Zhang
HGPrompt: Bridging Homogeneous and Heterogeneous Graphs for Few-Shot Prompt Learning. AAAI (2024)
Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhang
MultiGPrompt for Multi-Task Pre-Training and Prompting on Graphs. WWW (2024)
Zhongzhou Liu, Yuan Fang, Min Wu
Mitigating Popularity Bias for Users and Items with Fairness-centric Adaptive Recommendation. ACM Trans. Inf. Syst. 41 (3) (2023)
Fanwei Zhu, Yuan Fang, Kai Zhang, Kevin Chen-Chuan Chang, Hongtai Cao, Zhen Jiang, Minghui Wu
Unified and Incremental SimRank: Index-Free Approximation With Scheduled Principle. IEEE Trans. Knowl. Data Eng. 35 (3) (2023)
Xingtong Yu, Zhenghao Liu, Yuan Fang, Zemin Liu, Sihong Chen, Xinming Zhang
Generalized Graph Prompt: Toward a Unification of Pre-Training and Downstream Tasks on Graphs. CoRR (2023)
Trung-Kien Nguyen, Zemin Liu, Yuan Fang
Link Prediction on Latent Heterogeneous Graphs. CoRR (2023)
Zhihao Wen, Yuan Fang
Prompt Tuning on Graph-augmented Low-resource Text Classification. CoRR (2023)
Zemin Liu, Trung-Kien Nguyen, Yuan Fang
On Generalized Degree Fairness in Graph Neural Networks. CoRR (2023)
Zhongzhou Liu, Yuan Fang, Min Wu
Estimating Propensity for Causality-based Recommendation without Exposure Data. NeurIPS (2023)
Zemin Liu, Yuan Fang, Yong Liu, Vincent W. Zheng
Neighbor-Anchoring Adversarial Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35 (1) (2023)
Zhongzhou Liu, Yuan Fang, Min Wu
Estimating Propensity for Causality-based Recommendation without Exposure Data. CoRR (2023)
Zhihao Wen, Yuan Fang, Yihan Liu, Yang Guo, Shuji Hao
Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks. CIKM (2023)
Zemin Liu, Trung-Kien Nguyen, Yuan Fang
On Generalized Degree Fairness in Graph Neural Networks. AAAI (2023)
Zhongzhou Liu, Yuan Fang, Min Wu
Dual-View Preference Learning for Adaptive Recommendation. IEEE Trans. Knowl. Data Eng. 35 (11) (2023)
Deyu Bo, Yuan Fang, Yang Liu, Chuan Shi
Graph Contrastive Learning with Stable and Scalable Spectral Encoding. NeurIPS (2023)
Deyu Bo, Xiao Wang, Yang Liu, Yuan Fang, Yawen Li, Chuan Shi
A Survey on Spectral Graph Neural Networks. CoRR (2023)
Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang
Learning to Count Isomorphisms with Graph Neural Networks. CoRR (2023)
Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang
HGPROMPT: Bridging Homogeneous and Heterogeneous Graphs for Few-shot Prompt Learning. CoRR (2023)
Zhihao Wen, Yuan Fang
Augmenting Low-Resource Text Classification with Graph-Grounded Pre-training and Prompting. CoRR (2023)
Zhihao Wen, Yuan Fang
Augmenting Low-Resource Text Classification with Graph-Grounded Pre-training and Prompting. SIGIR (2023)
Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang
Learning to Count Isomorphisms with Graph Neural Networks. AAAI (2023)
Zemin Liu, Xingtong Yu, Yuan Fang, Xinming Zhang
GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks. WWW (2023)
Zemin Liu, Xingtong Yu, Yuan Fang, Xinming Zhang
GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks. CoRR (2023)
Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi
Towards Graph Foundation Models: A Survey and Beyond. CoRR (2023)
Trung-Kien Nguyen, Zemin Liu, Yuan Fang
Link Prediction on Latent Heterogeneous Graphs. WWW (2023)
Yugang Ji, Chuan Shi, Yuan Fang
Dynamic Meta-path Guided Temporal Heterogeneous Graph Neural Networks. World Sci. Annu. Rev. Artif. Intell. 1 (2023)
Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhang
MultiGPrompt for Multi-Task Pre-Training and Prompting on Graphs. CoRR (2023)
Zhihao Wen, Yuan Fang
TREND: TempoRal Event and Node Dynamics for Graph Representation Learning. CoRR (2022)
Ruichu Cai, Yuxuan Zhu, Xuexin Chen, Yuan Fang, Min Wu, Jie Qiao, Zhifeng Hao
On the Probability of Necessity and Sufficiency of Explaining Graph Neural Networks: A Lower Bound Optimization Approach. CoRR (2022)
Yahui Long, Min Wu, Yong Liu, Yuan Fang, Chee Keong Kwoh, Jinmiao Chen, Jiawei Luo, Xiaoli Li
Pre-training graph neural networks for link prediction in biomedical networks. Bioinform. 38 (8) (2022)
Fanwei Zhu, Yuan Fang, Kai Zhang, Kevin Chen-Chuan Chang, Hongtai Cao, Zhen Jiang, Minghui Wu
Unified and Incremental SimRank: Index-free Approximation with Scheduled Principle (Extended Abstract). ICDE (2022)
Zhihao Wen, Yuan Fang
TREND: TempoRal Event and Node Dynamics for Graph Representation Learning. WWW (2022)
Wentao Zhang, Yuan Fang, Zemin Liu, Min Wu, Xinming Zhang
mg2vec: Learning Relationship-Preserving Heterogeneous Graph Representations via Metagraph Embedding. IEEE Trans. Knowl. Data Eng. 34 (3) (2022)
Zemin Liu, Qiheng Mao, Chenghao Liu, Yuan Fang, Jianling Sun
On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks. WWW (2022)
Zemin Liu, Yuan Fang, Yong Liu, Vincent W. Zheng
Neighbor-Anchoring Adversarial Graph Neural Networks (Extended Abstract). ICDE (2022)
Sezin Kircali Ata, Min Wu, Yuan Fang, Le Ou-Yang, Chee Keong Kwoh, Xiaoli Li
Recent advances in network-based methods for disease gene prediction. Briefings Bioinform. 22 (4) (2021)
Xunqiang Jiang, Tianrui Jia, Yuan Fang, Chuan Shi, Zhe Lin, Hui Wang
Pre-training on Large-Scale Heterogeneous Graph. KDD (2021)
Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi
Node-wise Localization of Graph Neural Networks. IJCAI (2021)
Chuan Shi, Yuan Fang, Yanfang Ye, Jiawei Zhang
The 4th Workshop on Heterogeneous Information Network Analysis and Applications (HENA 2021). KDD (2021)
Sezin Kircali Ata, Yuan Fang, Min Wu, Jiaqi Shi, Chee Keong Kwoh, Xiaoli Li
Multi-View Collaborative Network Embedding. ACM Trans. Knowl. Discov. Data 15 (3) (2021)
Xuexin Chen, Ruichu Cai, Yuan Fang, Min Wu, Zijian Li, Zhifeng Hao
Motif Graph Neural Network. CoRR (2021)
Zhifeng Hao, Di Wu, Yuan Fang, Min Wu, Ruichu Cai, Xiaoli Li
Prediction of Synthetic Lethal Interactions in Human Cancers Using Multi-View Graph Auto-Encoder. IEEE J. Biomed. Health Informatics 25 (10) (2021)
Yuanfu Lu, Xunqiang Jiang, Yuan Fang, Chuan Shi
Learning to Pre-train Graph Neural Networks. AAAI (2021)
Siyong Xu, Cheng Yang, Chuan Shi, Yuan Fang, Yuxin Guo, Tianchi Yang, Luhao Zhang, Maodi Hu
Topic-aware Heterogeneous Graph Neural Network for Link Prediction. CIKM (2021)
Zhihao Wen, Yuan Fang, Zemin Liu
Meta-Inductive Node Classification across Graphs. SIGIR (2021)
Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi
Node-wise Localization of Graph Neural Networks. CoRR (2021)
Yugang Ji, Mingyang Yin, Hongxia Yang, Jingren Zhou, Vincent W. Zheng, Chuan Shi, Yuan Fang
Accelerating Large-Scale Heterogeneous Interaction Graph Embedding Learning via Importance Sampling. ACM Trans. Knowl. Discov. Data 15 (1) (2021)
Zemin Liu, Trung-Kien Nguyen, Yuan Fang
Tail-GNN: Tail-Node Graph Neural Networks. KDD (2021)
Zhihao Wen, Yuan Fang, Zemin Liu
Meta-Inductive Node Classification across Graphs. CoRR (2021)
Yuan Fang, Wenqing Lin, Vincent W. Zheng, Min Wu, Jiaqi Shi, Kevin Chen-Chuan Chang, Xiaoli Li
Metagraph-Based Learning on Heterogeneous Graphs. IEEE Trans. Knowl. Data Eng. 33 (1) (2021)
Yugang Ji, Tianrui Jia, Yuan Fang, Chuan Shi
Dynamic Heterogeneous Graph Embedding via Heterogeneous Hawkes Process. ECML/PKDD (1) (2021)
Xunqiang Jiang, Yuanfu Lu, Yuan Fang, Chuan Shi
Contrastive Pre-Training of GNNs on Heterogeneous Graphs. CIKM (2021)
Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi
Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph. AAAI (2021)
Ruichu Cai, Xuexin Chen, Yuan Fang, Min Wu, Yuexing Hao, Jonathan D. Wren
Dual-dropout graph convolutional network for predicting synthetic lethality in human cancers. Bioinform. 36 (16) (2020)
Chenghao Liu, Zhihao Wang, Doyen Sahoo, Yuan Fang, Kun Zhang, Steven C. H. Hoi
Adaptive Task Sampling for Meta-learning. ECCV (18) (2020)
Yugang Ji, Mingyang Yin, Yuan Fang, Hongxia Yang, Xiangwei Wang, Tianrui Jia, Chuan Shi
Temporal Heterogeneous Interaction Graph Embedding for Next-Item Recommendation. ECML/PKDD (3) (2020)
Yuanfu Lu, Ruobing Xie, Chuan Shi, Yuan Fang, Wei Wang, Xu Zhang, Leyu Lin
Social Influence Attentive Neural Network for Friend-Enhanced Recommendation. ECML/PKDD (4) (2020)
Sezin Kircali Ata, Yuan Fang, Min Wu, Jiaqi Shi, Chee Keong Kwoh, Xiaoli Li
Multi-View Collaborative Network Embedding. CoRR (2020)
Zemin Liu, Wentao Zhang, Yuan Fang, Xinming Zhang, Steven C. H. Hoi
Towards Locality-Aware Meta-Learning of Tail Node Embeddings on Networks. CIKM (2020)
Chenghao Liu, Zhihao Wang, Doyen Sahoo, Yuan Fang, Kun Zhang, Steven C. H. Hoi
Adaptive Task Sampling for Meta-Learning. CoRR (2020)
Xunqiang Jiang, Binbin Hu, Yuan Fang, Chuan Shi
Multiplex Memory Network for Collaborative Filtering. SDM (2020)
Yu-Neng Chuang, Chih-Ming Chen, Chuan-Ju Wang, Ming-Feng Tsai, Yuan Fang, Ee-Peng Lim
TPR: Text-aware Preference Ranking for Recommender Systems. CIKM (2020)
Yuanfu Lu, Yuan Fang, Chuan Shi
Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation. KDD (2020)
Yugang Ji, Chuan Shi, Yuan Fang, Xiangnan Kong, Mingyang Yin
Semi-supervised Co-Clustering on Attributed Heterogeneous Information Networks. Inf. Process. Manag. 57 (6) (2020)
Wentao Huang, Yuchen Li, Yuan Fang, Ju Fan, Hongxia Yang
BiANE: Bipartite Attributed Network Embedding. SIGIR (2020)
Sezin Kircali Ata, Min Wu, Yuan Fang, Le Ou-Yang, Chee Keong Kwoh, Xiaoli Li
Recent Advances in Network-based Methods for Disease Gene Prediction. CoRR (2020)
Binbin Hu, Yuan Fang, Chuan Shi
Adversarial Learning on Heterogeneous Information Networks. KDD (2019)
Duc-Trong Le, Hady W. Lauw, Yuan Fang
Correlation-Sensitive Next-Basket Recommendation. IJCAI (2019)
Duc-Trong Le, Hady W. Lauw, Yuan Fang
Modeling Contemporaneous Basket Sequences with Twin Networks for Next-Item Recommendation. IJCAI (2018)
Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Yuan Fang, Zhenjie Zhang, Kian-Lee Tan, Kevin Chen-Chuan Chang
Heterogeneous Embedding Propagation for Large-Scale E-Commerce User Alignment. ICDM (2018)
Duc-Trong Le, Hady Wirawan Lauw, Yuan Fang
Basket-Sensitive Personalized Item Recommendation. IJCAI (2017)
Yuan Fang, Kingsley Kuan, Jie Lin, Cheston Tan, Vijay Chandrasekhar
Object Detection Meets Knowledge Graphs. IJCAI (2017)
Kingsley Kuan, Gaurav Manek, Jie Lin, Yuan Fang, Vijay Chandrasekhar
Region average pooling for context-aware object detection. ICIP (2017)
Yuan Fang, Vincent W. Zheng, Kevin Chen-Chuan Chang
Learning to query: Focused web page harvesting for entity aspects. ICDE (2016)
Duc-Trong Le, Yuan Fang, Hady Wirawan Lauw
Modeling Sequential Preferences with Dynamic User and Context Factors. ECML/PKDD (2) (2016)
Yuan Fang, Wenqing Lin, Vincent Wenchen Zheng, Min Wu, Kevin Chen-Chuan Chang, Xiaoli Li
Semantic proximity search on graphs with metagraph-based learning. ICDE (2016)
Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying
Scheduled approximation for Personalized PageRank with Utility-based Hub Selection. VLDB J. 24 (5) (2015)
Aditi Adhikari, Vincent W. Zheng, Hong Cao, Miao Lin, Yuan Fang, Kevin Chen-Chuan Chang
IntelligShop: Enabling Intelligent Shopping in Malls through Location-Based Augmented Reality. ICDM Workshops (2015)
Yuan Fang, Kevin Chen-Chuan Chang, Hady Wirawan Lauw
Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically. ICML (2014)
Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying
Incremental and Accuracy-Aware Personalized PageRank through Scheduled Approximation. Proc. VLDB Endow. 6 (6) (2013)
Yuan Fang, Kevin Chen-Chuan Chang, Hady Wirawan Lauw
RoundTripRank: Graph-based proximity with importance and specificity? ICDE (2013)
Yuan Fang, Bo-June Paul Hsu, Kevin Chen-Chuan Chang
Confidence-aware graph regularization with heterogeneous pairwise features. SIGIR (2012)
Yuan Fang, Mafruz Zaman Ashrafi, See-Kiong Ng
Privacy beyond Single Sensitive Attribute. DEXA (1) (2011)
Yuan Fang, Kevin Chen-Chuan Chang
Searching patterns for relation extraction over the web: rediscovering the pattern-relation duality. WSDM (2011)
Yuan Fang, Chee-Yong Chan
Efficient Skyline Maintenance for Streaming Data with Partially-Ordered Domains. DASFAA (1) (2010)