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Privacy Threats Against Federated Matrix Factorization

Jul 03, 2020
Dashan Gao, Ben Tan, Ce Ju, Vincent W. Zheng, Qiang Yang

* 6 pages, 2 figures, 1 table, Accepted for Workshop on Federated Learning for Data Privacy and Confidentiality in Conjunction with IJCAI 2020 (FL-IJCAI'20) 

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Vertex-reinforced Random Walk for Network Embedding

Feb 11, 2020
Wenyi Xiao, Huan Zhao, Vincent W. Zheng, Yangqiu Song

* Accepted by SDM 2020 

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A Simple Regularization-based Algorithm for Learning Cross-Domain Word Embeddings

Feb 01, 2019
Wei Yang, Wei Lu, Vincent W. Zheng

* D17-1312, 2017, 2898-2904 
* 7 pages, accepted by EMNLP 2017 

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Deep Transfer Learning for Cross-domain Activity Recognition

Aug 19, 2018
Jindong Wang, Vincent W. Zheng, Yiqiang Chen, Meiyu Huang

* ICCSE 2018 best paper; 8 pages 

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A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications

Feb 02, 2018
Hongyun Cai, Vincent W. Zheng, Kevin Chen-Chuan Chang

* A 20-page comprehensive survey of graph/network embedding for over 150+ papers till year 2018. It provides systematic categorization of problems, techniques and applications. Accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE). Comments and suggestions are welcomed for continuously improving this survey 

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Topological Recurrent Neural Network for Diffusion Prediction

Nov 29, 2017
Jia Wang, Vincent W. Zheng, Zemin Liu, Kevin Chen-Chuan Chang

* In Proc. of The IEEE International Conference on Data Mining (ICDM '17), New Orleans, Louisiana, USA, 2017 

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From Node Embedding To Community Embedding

Sep 14, 2017
Vincent W. Zheng, Sandro Cavallari, Hongyun Cai, Kevin Chen-Chuan Chang, Erik Cambria

* Code available at https://github.com/andompesta/nodeembedding-to-communityembedding 

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Active Learning for Graph Embedding

May 15, 2017
Hongyun Cai, Vincent W. Zheng, Kevin Chen-Chuan Chang

* Technical Report 

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From Community Detection to Community Profiling

Jan 17, 2017
Hongyun Cai, Vincent W. Zheng, Fanwei Zhu, Kevin Chen-Chuan Chang, Zi Huang

* Technical report of a PVLDB 2017 paper 

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