How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study

25 February 2024

Papers citing "How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study"

7 / 7 papers shown

Title
FEATHERS: Federated Architecture and Hyperparameter Search Jonas Seng P. Prasad Martin Mundt D. Dhami Kristian Kersting FedML 34 3 0 24 Jun 2022
The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection Shubhankar Mohapatra Sajin Sasy Xi He Gautam Kamath Om Thakkar 109 32 0 09 Nov 2021
Hyperparameter Tuning with Renyi Differential Privacy Nicolas Papernot Thomas Steinke 123 118 0 07 Oct 2021
Federated Learning on Non-IID Data Silos: An Experimental Study Q. Li Yiqun Diao Quan Chen Bingsheng He FedML OOD 85 936 0 03 Feb 2021
Federated Bayesian Optimization via Thompson Sampling Zhongxiang Dai K. H. Low Patrick Jaillet FedML 79 109 0 20 Oct 2020
Real-time Federated Evolutionary Neural Architecture Search Hangyu Zhu Yaochu Jin FedML 131 70 0 04 Mar 2020
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 141 1,663 0 14 Apr 2018