Learning Rate Adaptation for Federated and Differentially Private Learning

11 September 2018

Papers citing "Learning Rate Adaptation for Federated and Differentially Private Learning"

8 / 8 papers shown

Title
FEATHERS: Federated Architecture and Hyperparameter Search Jonas Seng P. Prasad Martin Mundt Devendra Singh Dhami Kristian Kersting FedML 60 3 0 24 Jun 2022
Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis Yi Zhou Parikshit Ram Theodoros Salonidis Nathalie Baracaldo Horst Samulowitz Heiko Ludwig FedML 26 6 0 16 Feb 2022
FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning Yi Zhou Parikshit Ram Theodoros Salonidis Nathalie Baracaldo Horst Samulowitz Heiko Ludwig AI4CE 37 25 0 15 Dec 2021
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing M. Khodak Renbo Tu Tian Li Liam Li Maria-Florina Balcan Virginia Smith Ameet Talwalkar FedML 43 78 0 08 Jun 2021
Stochastic Adaptive Line Search for Differentially Private Optimization Chen Chen Jaewoo Lee 24 14 0 18 Aug 2020
A Systematic Literature Review on Federated Machine Learning: From A Software Engineering Perspective Sin Kit Lo Qinghua Lu Chen Wang Hye-Young Paik Liming Zhu FedML 50 83 0 22 Jul 2020
An Adaptive and Fast Convergent Approach to Differentially Private Deep Learning Zhiying Xu Shuyu Shi A. Liu Jun Zhao Lin Chen FedML 47 36 0 19 Dec 2019
Variational Bayes In Private Settings (VIPS) Mijung Park James R. Foulds Kamalika Chaudhuri Max Welling 21 42 0 01 Nov 2016