ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2006.08848
  4. Cited By
Personalized Federated Learning with Moreau Envelopes

Personalized Federated Learning with Moreau Envelopes

16 June 2020
Canh T. Dinh
N. H. Tran
Tuan Dung Nguyen
    FedML
ArXivPDFHTML

Papers citing "Personalized Federated Learning with Moreau Envelopes"

17 / 167 papers shown
Title
Opportunistic Federated Learning: An Exploration of Egocentric
  Collaboration for Pervasive Computing Applications
Opportunistic Federated Learning: An Exploration of Egocentric Collaboration for Pervasive Computing Applications
Sangsu Lee
Xi Zheng
Jie Hua
H. Vikalo
Christine Julien
FedML
26
25
0
24 Mar 2021
Private Cross-Silo Federated Learning for Extracting Vaccine Adverse
  Event Mentions
Private Cross-Silo Federated Learning for Extracting Vaccine Adverse Event Mentions
Pallika H. Kanani
Virendra J. Marathe
Daniel W. Peterson
R. Harpaz
Steve Bright
FedML
16
9
0
12 Mar 2021
Personalized Federated Learning using Hypernetworks
Personalized Federated Learning using Hypernetworks
Aviv Shamsian
Aviv Navon
Ethan Fetaya
Gal Chechik
FedML
41
324
0
08 Mar 2021
Towards Personalized Federated Learning
Towards Personalized Federated Learning
A. Tan
Han Yu
Li-zhen Cui
Qiang Yang
FedML
AI4CE
209
840
0
01 Mar 2021
Personalized Federated Learning: A Unified Framework and Universal
  Optimization Techniques
Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques
Filip Hanzely
Boxin Zhao
Mladen Kolar
FedML
27
52
0
19 Feb 2021
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts
Binbin Guo
Yuan Mei
Danyang Xiao
Weigang Wu
Ye Yin
Hongli Chang
MoE
47
22
0
31 Dec 2020
Fairness and Accuracy in Federated Learning
Fairness and Accuracy in Federated Learning
Wei Huang
Tianrui Li
Dexian Wang
Shengdong Du
Junbo Zhang
FedML
34
52
0
18 Dec 2020
FedADC: Accelerated Federated Learning with Drift Control
FedADC: Accelerated Federated Learning with Drift Control
Emre Ozfatura
Kerem Ozfatura
Deniz Gunduz
FedML
43
37
0
16 Dec 2020
Federated Composite Optimization
Federated Composite Optimization
Honglin Yuan
Manzil Zaheer
Sashank J. Reddi
FedML
32
58
0
17 Nov 2020
Collaborative Learning in the Jungle (Decentralized, Byzantine,
  Heterogeneous, Asynchronous and Nonconvex Learning)
Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)
El-Mahdi El-Mhamdi
Sadegh Farhadkhani
R. Guerraoui
Arsany Guirguis
L. Hoang
Sébastien Rouault
FedML
13
63
0
03 Aug 2020
Multi-Task Federated Learning for Personalised Deep Neural Networks in
  Edge Computing
Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing
Jed Mills
Jia Hu
Geyong Min
FedML
15
193
0
17 Jul 2020
Adaptive Personalized Federated Learning
Adaptive Personalized Federated Learning
Yuyang Deng
Mohammad Mahdi Kamani
M. Mahdavi
FedML
212
542
0
30 Mar 2020
Salvaging Federated Learning by Local Adaptation
Salvaging Federated Learning by Local Adaptation
Tao Yu
Eugene Bagdasaryan
Vitaly Shmatikov
FedML
14
260
0
12 Feb 2020
Robust Aggregation for Federated Learning
Robust Aggregation for Federated Learning
Krishna Pillutla
Sham Kakade
Zaïd Harchaoui
FedML
35
629
0
31 Dec 2019
FedPAQ: A Communication-Efficient Federated Learning Method with
  Periodic Averaging and Quantization
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization
Amirhossein Reisizadeh
Aryan Mokhtari
Hamed Hassani
Ali Jadbabaie
Ramtin Pedarsani
FedML
174
760
0
28 Sep 2019
New Convergence Aspects of Stochastic Gradient Algorithms
New Convergence Aspects of Stochastic Gradient Algorithms
Lam M. Nguyen
Phuong Ha Nguyen
Peter Richtárik
K. Scheinberg
Martin Takáč
Marten van Dijk
23
66
0
10 Nov 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
338
11,684
0
09 Mar 2017
Previous
1234