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FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data


Mar 05, 2021
Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, James Joshi, Heiko Ludwig


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Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning


Feb 01, 2021
Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan

* Accepted in AAAI 2021 

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IBM Federated Learning: an Enterprise Framework White Paper V0.1


Jul 22, 2020
Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas, Yi Zhou, Ali Anwar, Shashank Rajamoni, Yuya Ong, Jayaram Radhakrishnan, Ashish Verma, Mathieu Sinn, Mark Purcell, Ambrish Rawat, Tran Minh, Naoise Holohan, Supriyo Chakraborty, Shalisha Whitherspoon, Dean Steuer, Laura Wynter, Hifaz Hassan, Sean Laguna, Mikhail Yurochkin, Mayank Agarwal, Ebube Chuba, Annie Abay

* 17 pages 

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TiFL: A Tier-based Federated Learning System


Jan 25, 2020
Zheng Chai, Ahsan Ali, Syed Zawad, Stacey Truex, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Heiko Ludwig, Feng Yan, Yue Cheng


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HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning


Dec 12, 2019
Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Heiko Ludwig

* 12 pages, AISec 2019 

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Towards Federated Graph Learning for Collaborative Financial Crimes Detection


Oct 02, 2019
Toyotaro Suzumura, Yi Zhou, Natahalie Baracaldo, Guangnan Ye, Keith Houck, Ryo Kawahara, Ali Anwar, Lucia Larise Stavarache, Yuji Watanabe, Pablo Loyola, Daniel Klyashtorny, Heiko Ludwig, Kumar Bhaskaran


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A Hybrid Approach to Privacy-Preserving Federated Learning


Dec 07, 2018
Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang


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