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ORCIDYuan Fang 0001
Person information
- affiliation: Singapore Management University, School of Information Systems, Singapore
- affiliation: Institute for Infocomm Research, A'STAR, Singapor
Other persons with the same name
- Yuan Fang — disambiguation page
- Yuan Fang 0002
![[0000-0003-3815-1456]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0003-3815-1456")
— Chinese University of Hong Kong-Shenzhen (CUHK-SZ), Shenzhen, China (and 1 more) - Yuan Fang 0003 — China University of Geosciences, School of Land Science and Technology, Beijing, China
- Yuan Fang 0004 — Tongji University, Clean Energy Automotive Engineering Center, Shanghai, China
- Yuan Fang 0005 — Central South University, School of Information Science and Engineering, Changsha, China
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2020 – today
- 2025
[j21]Pengcheng Wei, Yuan Fang, Zhihao Wen, Zheng Xiao, Binbin Chen:
An end-to-end bi-objective approach to deep graph partitioning. Neural Networks 181: 106823 (2025)- 2024
- [j20]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): 2517-2532 (2024) - [j19]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. IEEE Trans. Knowl. Data Eng. 36(11): 6237-6250 (2024) - [j18]Zhihao Wen, Yuan Fang:
Prompt Tuning on Graph-Augmented Low-Resource Text Classification. IEEE Trans. Knowl. Data Eng. 36(12): 9080-9095 (2024) - [j17]Xuexin Chen, Ruichu Cai, Yuan Fang, Min Wu, Zijian Li, Zhifeng Hao:
Motif Graph Neural Network. IEEE Trans. Neural Networks Learn. Syst. 35(10): 14833-14847 (2024) - [c60]Xingtong Yu, Yuan Fang, Zemin Liu, Xinming Zhang:
HGPrompt: Bridging Homogeneous and Heterogeneous Graphs for Few-Shot Prompt Learning. AAAI 2024: 16578-16586 - [c59]Zhongzhou Liu, Hao Zhang, Kuicai Dong, Yuan Fang:
Collaborative Cross-modal Fusion with Large Language Model for Recommendation. CIKM 2024: 1565-1574 - [c58]Chandan Gautam, Sethupathy Parameswaran, Aditya Kane, Yuan Fang, Savitha Ramasamy, Suresh Sundaram, Sunil Sahu, Xiaoli Li:
Class Name Guided Out-of-Scope Intent Classification. EMNLP (Findings) 2024: 9100-9112 - [c57]Liu Ran, Zhongzhou Liu, Xiaoli Li, Yuan Fang:
Context-Aware Adapter Tuning for Few-Shot Relation Learning in Knowledge Graphs. EMNLP 2024: 17525-17537 - [c56]Jinggui Liang, Yuxia Wu, Yuan Fang, Hao Fei, Lizi Liao:
A Survey of Ontology Expansion for Conversational Understanding. EMNLP 2024: 18111-18127 - [c55]Zhiyuan Lu, Yuan Fang, Cheng Yang, Chuan Shi:
Heterogeneous Graph Transformer with Poly-Tokenization. IJCAI 2024: 2234-2242 - [c54]Jianyuan Bo, Yuan Fang:
Contrastive General Graph Matching with Adaptive Augmentation Sampling. IJCAI 2024: 3724-3732 - [c53]Amitoz Azad, Yuan Fang:
A Learned Generalized Geodesic Distance Function-Based Approach for Node Feature Augmentation on Graphs. KDD 2024: 49-58 - [c52]Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhang:
MultiGPrompt for Multi-Task Pre-Training and Prompting on Graphs. WWW 2024: 515-526 - [c51]Yuxia Wu, Yuan Fang, Lizi Liao:
On the Feasibility of Simple Transformer for Dynamic Graph Modeling. WWW 2024: 870-880 - [c50]Trung-Kien Nguyen, Yuan Fang:
Diffusion-based Negative Sampling on Graphs for Link Prediction. WWW 2024: 948-958 - [c49]Chuan Shi, Cheng Yang, Yuan Fang, Lichao Sun, Philip S. Yu:
Lecture-style Tutorial: Towards Graph Foundation Models. WWW (Companion Volume) 2024: 1264-1267 - [i34]Yuxia Wu, Yuan Fang, Lizi Liao:
On the Feasibility of Simple Transformer for Dynamic Graph Modeling. CoRR abs/2401.14009 (2024) - [i33]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 abs/2402.01440 (2024) - [i32]Zhihao Wen, Jie Zhang, Yuan Fang:
SIBO: A Simple Booster for Parameter-Efficient Fine-Tuning. CoRR abs/2402.11896 (2024) - [i31]Trung-Kien Nguyen, Yuan Fang:
Diffusion-based Negative Sampling on Graphs for Link Prediction. CoRR abs/2403.17259 (2024) - [i30]Zhihao Wen, Yuan Fang, Pengcheng Wei, Fayao Liu, Zhenghua Chen, Min Wu:
Temporal and Heterogeneous Graph Neural Network for Remaining Useful Life Prediction. CoRR abs/2405.04336 (2024) - [i29]Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhang:
Text-Free Multi-domain Graph Pre-training: Toward Graph Foundation Models. CoRR abs/2405.13934 (2024) - [i28]Jianyuan Bo, Yuan Fang:
Contrastive General Graph Matching with Adaptive Augmentation Sampling. CoRR abs/2406.17199 (2024) - [i27]Zhongzhou Liu, Hao Zhang, Kuicai Dong, Yuan Fang:
Collaborative Cross-modal Fusion with Large Language Model for Recommendation. CoRR abs/2408.08564 (2024) - [i26]Yuxia Wu, Shujie Li, Yuan Fang, Chuan Shi:
Exploring the Potential of Large Language Models for Heterophilic Graphs. CoRR abs/2408.14134 (2024) - [i25]Yuxia Wu, Yuan Fang, Lizi Liao:
Retrieval Augmented Generation for Dynamic Graph Modeling. CoRR abs/2408.14523 (2024) - [i24]Ran Liu, Zhongzhou Liu, Xiaoli Li, Hao Wu, Yuan Fang:
Diversified and Adaptive Negative Sampling on Knowledge Graphs. CoRR abs/2410.07592 (2024) - [i23]Ran Liu, Zhongzhou Liu, Xiao-Li Li, Yuan Fang:
Context-Aware Adapter Tuning for Few-Shot Relation Learning in Knowledge Graphs. CoRR abs/2410.09123 (2024) - [i22]Jinggui Liang, Yuxia Wu, Yuan Fang, Hao Fei, Lizi Liao:
A Survey of Ontology Expansion for Conversational Understanding. CoRR abs/2410.15019 (2024) - 2023
- [j16]Zemin Liu, Yuan Fang, Yong Liu, Vincent W. Zheng:
Neighbor-Anchoring Adversarial Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35(1): 784-795 (2023) - [j15]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): 3195-3210 (2023) - [j14]Zhongzhou Liu, Yuan Fang, Min Wu:
Dual-View Preference Learning for Adaptive Recommendation. IEEE Trans. Knowl. Data Eng. 35(11): 11316-11327 (2023) - [j13]Zhongzhou Liu, Yuan Fang, Min Wu:
Mitigating Popularity Bias for Users and Items with Fairness-centric Adaptive Recommendation. ACM Trans. Inf. Syst. 41(3): 55:1-55:27 (2023) - [j12]Yugang Ji, Chuan Shi, Yuan Fang:
Dynamic Meta-path Guided Temporal Heterogeneous Graph Neural Networks. World Sci. Annu. Rev. Artif. Intell. 1: 2350002:1-2350002:22 (2023) - [c48]Zemin Liu, Trung-Kien Nguyen, Yuan Fang:
On Generalized Degree Fairness in Graph Neural Networks. AAAI 2023: 4525-4533 - [c47]Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang:
Learning to Count Isomorphisms with Graph Neural Networks. AAAI 2023: 4845-4853 - [c46]Zhihao Wen, Yuan Fang, Yihan Liu, Yang Guo, Shuji Hao:
Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks. CIKM 2023: 4864-4870 - [c45]Deyu Bo, Yuan Fang, Yang Liu, Chuan Shi:
Graph Contrastive Learning with Stable and Scalable Spectral Encoding. NeurIPS 2023 - [c44]Zhongzhou Liu, Yuan Fang, Min Wu:
Estimating Propensity for Causality-based Recommendation without Exposure Data. NeurIPS 2023 - [c43]Zhihao Wen, Yuan Fang:
Augmenting Low-Resource Text Classification with Graph-Grounded Pre-training and Prompting. SIGIR 2023: 506-516 - [c42]Trung-Kien Nguyen, Zemin Liu, Yuan Fang:
Link Prediction on Latent Heterogeneous Graphs. WWW 2023: 263-273 - [c41]Zemin Liu, Xingtong Yu, Yuan Fang, Xinming Zhang:
GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks. WWW 2023: 417-428 - [i21]Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang:
Learning to Count Isomorphisms with Graph Neural Networks. CoRR abs/2302.03266 (2023) - [i20]Zemin Liu, Trung-Kien Nguyen, Yuan Fang:
On Generalized Degree Fairness in Graph Neural Networks. CoRR abs/2302.03881 (2023) - [i19]Deyu Bo, Xiao Wang, Yang Liu, Yuan Fang, Yawen Li, Chuan Shi:
A Survey on Spectral Graph Neural Networks. CoRR abs/2302.05631 (2023) - [i18]Zemin Liu, Xingtong Yu, Yuan Fang, Xinming Zhang:
GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks. CoRR abs/2302.08043 (2023) - [i17]Trung-Kien Nguyen, Zemin Liu, Yuan Fang:
Link Prediction on Latent Heterogeneous Graphs. CoRR abs/2302.10432 (2023) - [i16]Zhihao Wen, Yuan Fang:
Augmenting Low-Resource Text Classification with Graph-Grounded Pre-training and Prompting. CoRR abs/2305.03324 (2023) - [i15]Zhihao Wen, Yuan Fang:
Prompt Tuning on Graph-augmented Low-resource Text Classification. CoRR abs/2307.10230 (2023) - [i14]Zhihao Wen, Yuan Fang, Yihan Liu, Yang Guo, Shuji Hao:
Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks. CoRR abs/2308.10028 (2023) - [i13]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 abs/2310.11829 (2023) - [i12]Zhongzhou Liu, Yuan Fang, Min Wu:
Estimating Propensity for Causality-based Recommendation without Exposure Data. CoRR abs/2310.20388 (2023) - [i11]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 abs/2311.15317 (2023) - [i10]Xingtong Yu, Yuan Fang, Zemin Liu, Xinming Zhang:
HGPROMPT: Bridging Homogeneous and Heterogeneous Graphs for Few-shot Prompt Learning. CoRR abs/2312.01878 (2023) - [i9]Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhang:
MultiGPrompt for Multi-Task Pre-Training and Prompting on Graphs. CoRR abs/2312.03731 (2023) - 2022
- [j11]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): 2254-2262 (2022) - [j10]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): 1317-1329 (2022) - [c40]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: 1569-1570 - [c39]Zemin Liu, Yuan Fang, Yong Liu, Vincent W. Zheng:
Neighbor-Anchoring Adversarial Graph Neural Networks (Extended Abstract). ICDE 2022: 1571-1572 - [c38]Tiancheng Huang, Donglin Wang, Yuan Fang, Zhengyu Chen:
End-to-End Open-Set Semi-Supervised Node Classification with Out-of-Distribution Detection. IJCAI 2022: 2087-2093 - [c37]Zhihao Wen, Yuan Fang:
TREND: TempoRal Event and Node Dynamics for Graph Representation Learning. WWW 2022: 1159-1169 - [c36]Zemin Liu, Qiheng Mao, Chenghao Liu, Yuan Fang, Jianling Sun:
On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks. WWW 2022: 1506-1516 - [i8]Zhihao Wen, Yuan Fang:
TREND: TempoRal Event and Node Dynamics for Graph Representation Learning. CoRR abs/2203.14303 (2022) - [i7]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 abs/2212.07056 (2022) - 2021
- [j9]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) - [j8]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): 4041-4051 (2021) - [j7]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): 10:1-10:23 (2021) - [j6]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): 39:1-39:18 (2021) - [j5]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): 154-168 (2021) - [c35]Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi:
Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph. AAAI 2021: 4267-4275 - [c34]Yuanfu Lu, Xunqiang Jiang, Yuan Fang, Chuan Shi:
Learning to Pre-train Graph Neural Networks. AAAI 2021: 4276-4284 - [c33]Xunqiang Jiang, Yuanfu Lu, Yuan Fang, Chuan Shi:
Contrastive Pre-Training of GNNs on Heterogeneous Graphs. CIKM 2021: 803-812 - [c32]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: 2261-2270 - [c31]Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi:
Node-wise Localization of Graph Neural Networks. IJCAI 2021: 1520-1526 - [c30]Xunqiang Jiang, Tianrui Jia, Yuan Fang, Chuan Shi, Zhe Lin, Hui Wang:
Pre-training on Large-Scale Heterogeneous Graph. KDD 2021: 756-766 - [c29]Zemin Liu, Trung-Kien Nguyen, Yuan Fang:
Tail-GNN: Tail-Node Graph Neural Networks. KDD 2021: 1109-1119 - [c28]Chuan Shi, Yuan Fang, Yanfang Ye, Jiawei Zhang:
The 4th Workshop on Heterogeneous Information Network Analysis and Applications (HENA 2021). KDD 2021: 4157-4158 - [c27]Yugang Ji, Tianrui Jia, Yuan Fang, Chuan Shi:
Dynamic Heterogeneous Graph Embedding via Heterogeneous Hawkes Process. ECML/PKDD (1) 2021: 388-403 - [c26]Zhihao Wen, Yuan Fang, Zemin Liu:
Meta-Inductive Node Classification across Graphs. SIGIR 2021: 1219-1228 - [i6]Zhihao Wen, Yuan Fang, Zemin Liu:
Meta-Inductive Node Classification across Graphs. CoRR abs/2105.06725 (2021) - [i5]Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi:
Node-wise Localization of Graph Neural Networks. CoRR abs/2110.14322 (2021) - [i4]Xuexin Chen, Ruichu Cai, Yuan Fang, Min Wu, Zijian Li, Zhifeng Hao:
Motif Graph Neural Network. CoRR abs/2112.14900 (2021) - 2020
- [j4]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): 4458-4465 (2020) - [j3]Yugang Ji, Chuan Shi, Yuan Fang, Xiangnan Kong, Mingyang Yin:
Semi-supervised Co-Clustering on Attributed Heterogeneous Information Networks. Inf. Process. Manag. 57(6): 102338 (2020) - [c25]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: 215-224 - [c24]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: 975-984 - [c23]Chenghao Liu, Zhihao Wang, Doyen Sahoo, Yuan Fang, Kun Zhang, Steven C. H. Hoi:
Adaptive Task Sampling for Meta-learning. ECCV (18) 2020: 752-769 - [c22]Yuanfu Lu, Yuan Fang, Chuan Shi:
Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation. KDD 2020: 1563-1573 - [c21]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: 3-18 - [c20]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: 314-329 - [c19]Xunqiang Jiang, Binbin Hu, Yuan Fang, Chuan Shi:
Multiplex Memory Network for Collaborative Filtering. SDM 2020: 91-99 - [c18]Wentao Huang, Yuchen Li, Yuan Fang, Ju Fan, Hongxia Yang:
BiANE: Bipartite Attributed Network Embedding. SIGIR 2020: 149-158 - [i3]Sezin Kircali Ata, Yuan Fang, Min Wu, Jiaqi Shi, Chee Keong Kwoh, Xiaoli Li:
Multi-View Collaborative Network Embedding. CoRR abs/2005.08189 (2020) - [i2]Chenghao Liu, Zhihao Wang, Doyen Sahoo, Yuan Fang, Kun Zhang, Steven C. H. Hoi:
Adaptive Task Sampling for Meta-Learning. CoRR abs/2007.08735 (2020) - [i1]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 abs/2007.10848 (2020)
2010 – 2019
- 2019
- [c17]Duc-Trong Le, Hady W. Lauw, Yuan Fang:
Correlation-Sensitive Next-Basket Recommendation. IJCAI 2019: 2808-2814 - [c16]Binbin Hu, Yuan Fang, Chuan Shi:
Adversarial Learning on Heterogeneous Information Networks. KDD 2019: 120-129 - 2018
- [c15]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: 1434-1439 - [c14]Duc-Trong Le, Hady W. Lauw, Yuan Fang:
Modeling Contemporaneous Basket Sequences with Twin Networks for Next-Item Recommendation. IJCAI 2018: 3414-3420 - 2017
- [c13]Kingsley Kuan, Gaurav Manek, Jie Lin, Yuan Fang, Vijay Chandrasekhar:
Region average pooling for context-aware object detection. ICIP 2017: 1347-1351 - [c12]Yuan Fang, Kingsley Kuan, Jie Lin, Cheston Tan, Vijay Chandrasekhar:
Object Detection Meets Knowledge Graphs. IJCAI 2017: 1661-1667 - [c11]Duc-Trong Le, Hady Wirawan Lauw, Yuan Fang:
Basket-Sensitive Personalized Item Recommendation. IJCAI 2017: 2060-2066 - 2016
- [c10]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: 277-288 - [c9]Yuan Fang, Vincent W. Zheng, Kevin Chen-Chuan Chang:
Learning to query: Focused web page harvesting for entity aspects. ICDE 2016: 1002-1013 - [c8]Duc-Trong Le, Yuan Fang, Hady Wirawan Lauw:
Modeling Sequential Preferences with Dynamic User and Context Factors. ECML/PKDD (2) 2016: 145-161 - 2015
- [j2]Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying:
Scheduled approximation for Personalized PageRank with Utility-based Hub Selection. VLDB J. 24(5): 655-679 (2015) - [c7]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: 1604-1607 - 2014
- [b1]Yuan Fang:
Walking forward and backward: towards graph-based searching and mining. University of Illinois Urbana-Champaign, USA, 2014 - [c6]Yuan Fang, Kevin Chen-Chuan Chang, Hady Wirawan Lauw:
Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically. ICML 2014: 406-414 - 2013
- [j1]Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying:
Incremental and Accuracy-Aware Personalized PageRank through Scheduled Approximation. Proc. VLDB Endow. 6(6): 481-492 (2013) - [c5]Yuan Fang, Kevin Chen-Chuan Chang, Hady Wirawan Lauw:
RoundTripRank: Graph-based proximity with importance and specificity? ICDE 2013: 613-624 - 2012
- [c4]Yuan Fang, Bo-June Paul Hsu, Kevin Chen-Chuan Chang:
Confidence-aware graph regularization with heterogeneous pairwise features. SIGIR 2012: 951-960 - 2011
- [c3]Yuan Fang, Mafruz Zaman Ashrafi, See-Kiong Ng:
Privacy beyond Single Sensitive Attribute. DEXA (1) 2011: 187-201 - [c2]Yuan Fang, Kevin Chen-Chuan Chang:
Searching patterns for relation extraction over the web: rediscovering the pattern-relation duality. WSDM 2011: 825-834 - 2010
- [c1]Yuan Fang, Chee-Yong Chan:
Efficient Skyline Maintenance for Streaming Data with Partially-Ordered Domains. DASFAA (1) 2010: 322-336
Coauthor Index
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