PBM-VFL: Vertical Federated Learning with Feature and Sample Privacy

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PBM-VFL: Vertical Federated Learning with Feature and Sample Privacy

23 January 2025

Timothy Castiglia

Stacy Patterson

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Papers citing "PBM-VFL: Vertical Federated Learning with Feature and Sample Privacy"

16 / 16 papers shown

Title
Randomized Quantization is All You Need for Differential Privacy in Federated Learning Yeojoon Youn Zihao Hu Juba Ziani Jacob D. Abernethy FedML 156 28 0 20 Jun 2023
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split ModelsIACR Cryptology ePrint Archive (IACR ePrint), 2023 Songze Li Duanyi Yao Jin Liu FedML 295 41 0 26 Apr 2023
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism DesignInternational Conference on Machine Learning (ICML), 2022 Chuan Guo Kamalika Chaudhuri Pierre Stock Michael G. Rabbat FedML 281 7 0 08 Nov 2022
Differentially Private Vertical Federated ClusteringProceedings of the VLDB Endowment (PVLDB), 2022 Zitao Li Tianhao Wang Ninghui Li FedML 259 23 0 02 Aug 2022
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data Runhua Xu Nathalie Baracaldo Yi Zhou Ali Anwar J. Joshi Heiko Ludwig FedML 154 91 0 05 Mar 2021
LDP-Fed: Federated Learning with Local Differential Privacy Stacey Truex Ling Liu Ka-Ho Chow Mehmet Emre Gursoy Wenqi Wei FedML 186 468 0 05 Jun 2020
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification Chaochao Chen Jun Zhou Longfei Zheng Huiwen Wu Lingjuan Lyu Hongzhi Zhang Bingzhe Wu Ziqi Liu L. xilinx Wang Xiaolin Zheng FedML 351 114 0 25 May 2020
Inverting Gradients -- How easy is it to break privacy in federated learning?Neural Information Processing Systems (NeurIPS), 2020 Jonas Geiping Hartmut Bauermeister Hannah Dröge Michael Moeller FedML 607 1,458 0 31 Mar 2020
Federated Learning with Differential Privacy: Algorithms and Performance AnalysisIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2019 Kang Wei Jun Li Ming Ding Chuan Ma Heng Yang Farokhi Farhad Shi Jin Tony Q.S. Quek H. Vincent Poor FedML 473 1,945 0 01 Nov 2019
A Hybrid Approach to Privacy-Preserving Federated Learning Stacey Truex Nathalie Baracaldo Ali Anwar Thomas Steinke Heiko Ludwig Rui Zhang Yi Zhou FedML 194 995 0 07 Dec 2018
cpSGD: Communication-efficient and differentially-private distributed SGD Naman Agarwal A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 260 524 0 27 May 2018
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption Lam M. Nguyen Phuong Ha Nguyen Marten van Dijk Peter Richtárik K. Scheinberg Martin Takáč 208 241 0 11 Feb 2018
Practical Secure Aggregation for Federated Learning on User-Held Data Keith Bonawitz Vladimir Ivanov Ben Kreuter Antonio Marcedone H. B. McMahan Sarvar Patel Daniel Ramage Aaron Segal Karn Seth FedML 200 584 0 14 Nov 2016
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 749 3,509 0 15 Jun 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 1.4K 21,214 0 17 Feb 2016
Understanding Deep Image Representations by Inverting ThemComputer Vision and Pattern Recognition (CVPR), 2014 Aravindh Mahendran Andrea Vedaldi FAtt 479 2,041 0 26 Nov 2014