Publications

• FederatedScope: A Flexible Federated Learning Platform for Heterogeneity. VLDB’23 pdf

  Yuexiang Xie, Zhen Wang, Dawei Gao, Daoyuan Chen, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou.

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• pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning. NeurIPS’22. pdf

  Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding.

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• FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning. KDD’22. pdf

  Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou.

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• Federated Matrix Factorization with Privacy Guarantee. VLDB’21. pdf

  Zitao Li, Bolin Ding, Ce Zhang, Ninghui Li, Jingren Zhou

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• Collecting and Analyzing Data Jointly from Multiple Services under Local Differential Privacy. VLDB’20. pdf

  Min Xu, Bolin Ding, Tianhao Wang, Jingren Zhou.

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• Improving Utility and Security of the Shuffler-based Differential Privacy. VLDB’20. pdf

  Tianhao Wang, Bolin Ding, Min Xu, Zhicong Huang, Cheng Hong, Jingren Zhou, Ninghui Li, Somesh Jha.

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• Answering Multi-Dimensional Analytical Queries under Local Differential Privacy. SIGMOD’19. pdf

  Tianhao Wang, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang, Ninghui Li, Somesh Jha.

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• DPSAaS: Multi-Dimensional Data Sharing and Analytics as Services under Local Differential Privacy. VLDB’19. pdf

  Min Xu, Tianhao Wang, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang.

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