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Share Your Representation Only: Guaranteed Improvement of the
  Privacy-Utility Tradeoff in Federated Learning

Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning

11 September 2023
Zebang Shen
Jiayuan Ye
Anmin Kang
Hamed Hassani
Reza Shokri
    FedML
ArXiv (abs)PDFHTMLGithub (16★)

Papers citing "Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning"

27 / 27 papers shown
Title
Differential Privacy Personalized Federated Learning Based on Dynamically Sparsified Client Updates
Differential Privacy Personalized Federated Learning Based on Dynamically Sparsified Client Updates
Chuanyin Wang
Yifei Zhang
Neng Gao
Qiang Luo
FedML
198
0
0
12 Mar 2025
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning
Liam Collins
Hamed Hassani
Aryan Mokhtari
Sanjay Shakkottai
FedML
72
79
0
27 May 2022
Federated Learning with Partial Model Personalization
Federated Learning with Partial Model Personalization
Krishna Pillutla
Kshitiz Malik
Abdel-rahman Mohamed
Michael G. Rabbat
Maziar Sanjabi
Lin Xiao
FedML
99
168
0
08 Apr 2022
Personalization Improves Privacy-Accuracy Tradeoffs in Federated
  Learning
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning
A. Bietti
Chen-Yu Wei
Miroslav Dudík
John Langford
Zhiwei Steven Wu
FedML
83
50
0
10 Feb 2022
Federated Learning Based on Dynamic Regularization
Federated Learning Based on Dynamic Regularization
D. A. E. Acar
Yue Zhao
Ramon Matas Navarro
Matthew Mattina
P. Whatmough
Venkatesh Saligrama
FedML
76
781
0
08 Nov 2021
Private Multi-Task Learning: Formulation and Applications to Federated
  Learning
Private Multi-Task Learning: Formulation and Applications to Federated Learning
Shengyuan Hu
Zhiwei Steven Wu
Virginia Smith
FedML
76
20
0
30 Aug 2021
Convergence and Accuracy Trade-Offs in Federated Learning and
  Meta-Learning
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning
Zachary B. Charles
Jakub Konecný
FedML
98
64
0
08 Mar 2021
Learning with User-Level Privacy
Learning with User-Level Privacy
Daniel Levy
Ziteng Sun
Kareem Amin
Satyen Kale
Alex Kulesza
M. Mohri
A. Suresh
FedML
79
91
0
23 Feb 2021
Federated Reconstruction: Partially Local Federated Learning
Federated Reconstruction: Partially Local Federated Learning
K. Singhal
Hakim Sidahmed
Zachary Garrett
Shanshan Wu
Keith Rush
Sushant Prakash
FedML
69
143
0
05 Feb 2021
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
390
18,897
0
13 Feb 2020
Salvaging Federated Learning by Local Adaptation
Salvaging Federated Learning by Local Adaptation
Tao Yu
Eugene Bagdasaryan
Vitaly Shmatikov
FedML
66
267
0
12 Feb 2020
Federated Learning with Personalization Layers
Federated Learning with Personalization Layers
Manoj Ghuhan Arivazhagan
V. Aggarwal
Aaditya Kumar Singh
Sunav Choudhary
FedML
96
840
0
02 Dec 2019
Federated Evaluation of On-device Personalization
Federated Evaluation of On-device Personalization
Kangkang Wang
Rajiv Mathews
Chloé Kiddon
Hubert Eichner
F. Beaufays
Daniel Ramage
FedML
82
286
0
22 Oct 2019
Improving Federated Learning Personalization via Model Agnostic Meta
  Learning
Improving Federated Learning Personalization via Model Agnostic Meta Learning
Yihan Jiang
Jakub Konecný
Keith Rush
Sreeram Kannan
FedML
86
602
0
27 Sep 2019
Rényi Differential Privacy of the Sampled Gaussian Mechanism
Rényi Differential Privacy of the Sampled Gaussian Mechanism
Ilya Mironov
Kunal Talwar
Li Zhang
96
287
0
28 Aug 2019
cpSGD: Communication-efficient and differentially-private distributed
  SGD
cpSGD: Communication-efficient and differentially-private distributed SGD
Naman Agarwal
A. Suresh
Felix X. Yu
Sanjiv Kumar
H. B. McMahan
FedML
136
491
0
27 May 2018
Collecting Telemetry Data Privately
Collecting Telemetry Data Privately
Bolin Ding
Janardhan Kulkarni
Sergey Yekhanin
62
689
0
05 Dec 2017
Deep Learning with Differential Privacy
Deep Learning with Differential Privacy
Martín Abadi
Andy Chu
Ian Goodfellow
H. B. McMahan
Ilya Mironov
Kunal Talwar
Li Zhang
FedMLSyDa
216
6,172
0
01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized
  Data
Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
FedML
408
17,615
0
17 Feb 2016
The Benefit of Multitask Representation Learning
The Benefit of Multitask Representation Learning
Andreas Maurer
Massimiliano Pontil
Bernardino Romera-Paredes
SSL
109
376
0
23 May 2015
Improved Distributed Principal Component Analysis
Improved Distributed Principal Component Analysis
Maria-Florina Balcan
Vandana Kanchanapally
Yingyu Liang
David P. Woodruff
88
149
0
25 Aug 2014
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
Ulfar Erlingsson
Vasyl Pihur
Aleksandra Korolova
109
2,001
0
25 Jul 2014
Private Matchings and Allocations
Private Matchings and Allocations
Justin Hsu
Zhiyi Huang
Aaron Roth
Tim Roughgarden
Zhiwei Steven Wu
79
97
0
12 Nov 2013
The Noisy Power Method: A Meta Algorithm with Applications
The Noisy Power Method: A Meta Algorithm with Applications
Moritz Hardt
Eric Price
128
205
0
11 Nov 2013
Low-rank Matrix Completion using Alternating Minimization
Low-rank Matrix Completion using Alternating Minimization
Prateek Jain
Praneeth Netrapalli
Sujay Sanghavi
224
1,068
0
03 Dec 2012
Mechanism Design in Large Games: Incentives and Privacy
Michael Kearns
Mallesh M. Pai
Aaron Roth
Jonathan R. Ullman
154
184
0
17 Jul 2012
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OODSSL
284
12,460
0
24 Jun 2012
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