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Differentially Private Adaptive Optimization with Delayed
  Preconditioners

Differentially Private Adaptive Optimization with Delayed Preconditioners

1 December 2022
Tian Li
Manzil Zaheer
Ziyu Liu
Sashank J. Reddi
H. B. McMahan
Virginia Smith
ArXivPDFHTML

Papers citing "Differentially Private Adaptive Optimization with Delayed Preconditioners"

10 / 10 papers shown
Title
Communication-Efficient and Privacy-Preserving Decentralized
  Meta-Learning
Communication-Efficient and Privacy-Preserving Decentralized Meta-Learning
Hansi Yang
James T. Kwok
48
0
0
19 Jun 2024
DPDR: Gradient Decomposition and Reconstruction for Differentially
  Private Deep Learning
DPDR: Gradient Decomposition and Reconstruction for Differentially Private Deep Learning
Yixuan Liu
Li Xiong
Yuhan Liu
Yujie Gu
Ruixuan Liu
Hong Chen
38
1
0
04 Jun 2024
On the Convergence of Differentially-Private Fine-tuning: To Linearly
  Probe or to Fully Fine-tune?
On the Convergence of Differentially-Private Fine-tuning: To Linearly Probe or to Fully Fine-tune?
Shuqi Ke
Charlie Hou
Giulia Fanti
Sewoong Oh
34
4
0
29 Feb 2024
Momentum Approximation in Asynchronous Private Federated Learning
Momentum Approximation in Asynchronous Private Federated Learning
Tao Yu
Congzheng Song
Jianyu Wang
Mona Chitnis
FedML
30
1
0
14 Feb 2024
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias
  Correction)
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction)
Qiaoyue Tang
Frederick Shpilevskiy
Mathias Lécuyer
27
13
0
21 Dec 2023
Client-Level Differential Privacy via Adaptive Intermediary in Federated
  Medical Imaging
Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical Imaging
Meirui Jiang
Yuan Zhong
Anjie Le
Xiaoxiao Li
Qianming Dou
FedML
37
5
0
24 Jul 2023
Practical Differentially Private Hyperparameter Tuning with Subsampling
Practical Differentially Private Hyperparameter Tuning with Subsampling
A. Koskela
Tejas D. Kulkarni
36
14
0
27 Jan 2023
A New Linear Scaling Rule for Private Adaptive Hyperparameter
  Optimization
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization
Ashwinee Panda
Xinyu Tang
Saeed Mahloujifar
Vikash Sehwag
Prateek Mittal
24
11
0
08 Dec 2022
Practical and Private (Deep) Learning without Sampling or Shuffling
Practical and Private (Deep) Learning without Sampling or Shuffling
Peter Kairouz
Brendan McMahan
Shuang Song
Om Thakkar
Abhradeep Thakurta
Zheng Xu
FedML
178
154
0
26 Feb 2021
A new regret analysis for Adam-type algorithms
A new regret analysis for Adam-type algorithms
Ahmet Alacaoglu
Yura Malitsky
P. Mertikopoulos
V. Cevher
ODL
40
42
0
21 Mar 2020
1