Differentially Private Adaptive Optimization with Delayed
Preconditioners

Differentially Private Adaptive Optimization with Delayed Preconditioners

1 December 2022

Sashank J. Reddi

Papers citing "Differentially Private Adaptive Optimization with Delayed Preconditioners"

10 / 10 papers shown

Title
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 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? Shuqi Ke Charlie Hou Giulia Fanti Sewoong Oh 34 4 0 29 Feb 2024
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) Qiaoyue Tang Frederick Shpilevskiy Mathias Lécuyer 27 13 0 21 Dec 2023
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 A. Koskela Tejas D. Kulkarni 36 14 0 27 Jan 2023
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 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 Ahmet Alacaoglu Yura Malitsky P. Mertikopoulos V. Cevher ODL 40 42 0 21 Mar 2020