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Window-based Model Averaging Improves Generalization in Heterogeneous
  Federated Learning
v1v2 (latest)

Window-based Model Averaging Improves Generalization in Heterogeneous Federated Learning

2 October 2023
Debora Caldarola
Barbara Caputo
Marco Ciccone
    FedML
ArXiv (abs)PDFHTML

Papers citing "Window-based Model Averaging Improves Generalization in Heterogeneous Federated Learning"

24 / 24 papers shown
Title
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs
Yan Sun
Li Shen
Dacheng Tao
FedML
78
0
0
27 Sep 2024
Stop Wasting My Time! Saving Days of ImageNet and BERT Training with
  Latest Weight Averaging
Stop Wasting My Time! Saving Days of ImageNet and BERT Training with Latest Weight Averaging
Jean Kaddour
MoMe3DH
62
41
0
29 Sep 2022
AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias
  Estimation
AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation
Farshid Varno
Marzie Saghayi
Laya Rafiee
Sharut Gupta
Stan Matwin
Mohammad Havaei
FedML
122
31
0
27 Apr 2022
Federated Learning Based on Dynamic Regularization
Federated Learning Based on Dynamic Regularization
D. A. E. Acar
Yue Zhao
Ramon Matas Navarro
Matthew Mattina
P. Whatmough
Venkatesh Saligrama
FedML
71
776
0
08 Nov 2021
FedJAX: Federated learning simulation with JAX
FedJAX: Federated learning simulation with JAX
Jae Hun Ro
A. Suresh
Ke Wu
FedML
90
49
0
04 Aug 2021
No Fear of Heterogeneity: Classifier Calibration for Federated Learning
  with Non-IID Data
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data
Mi Luo
Fei Chen
Dapeng Hu
Yifan Zhang
Jian Liang
Jiashi Feng
FedML
83
340
0
09 Jun 2021
ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning
  of Deep Neural Networks
ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks
Jungmin Kwon
Jeongseop Kim
Hyunseong Park
I. Choi
96
290
0
23 Feb 2021
FedADC: Accelerated Federated Learning with Drift Control
FedADC: Accelerated Federated Learning with Drift Control
Emre Ozfatura
Kerem Ozfatura
Deniz Gunduz
FedML
90
38
0
16 Dec 2020
Sharpness-Aware Minimization for Efficiently Improving Generalization
Sharpness-Aware Minimization for Efficiently Improving Generalization
Pierre Foret
Ariel Kleiner
H. Mobahi
Behnam Neyshabur
AAML
192
1,350
0
03 Oct 2020
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning
Sai Praneeth Karimireddy
Martin Jaggi
Satyen Kale
M. Mohri
Sashank J. Reddi
Sebastian U. Stich
A. Suresh
FedML
133
217
0
08 Aug 2020
Google Landmarks Dataset v2 -- A Large-Scale Benchmark for
  Instance-Level Recognition and Retrieval
Google Landmarks Dataset v2 -- A Large-Scale Benchmark for Instance-Level Recognition and Retrieval
Tobias Weyand
A. Araújo
Bingyi Cao
Jack Sim
78
369
0
03 Apr 2020
Federated Visual Classification with Real-World Data Distribution
Federated Visual Classification with Real-World Data Distribution
T. Hsu
Qi
Matthew Brown
FedML
124
202
0
18 Mar 2020
Adaptive Federated Optimization
Adaptive Federated Optimization
Sashank J. Reddi
Zachary B. Charles
Manzil Zaheer
Zachary Garrett
Keith Rush
Jakub Konecný
Sanjiv Kumar
H. B. McMahan
FedML
179
1,437
0
29 Feb 2020
Personalized Federated Learning: A Meta-Learning Approach
Personalized Federated Learning: A Meta-Learning Approach
Alireza Fallah
Aryan Mokhtari
Asuman Ozdaglar
FedML
157
569
0
19 Feb 2020
Advances and Open Problems in Federated Learning
Advances and Open Problems in Federated Learning
Peter Kairouz
H. B. McMahan
Brendan Avent
A. Bellet
M. Bennis
...
Zheng Xu
Qiang Yang
Felix X. Yu
Han Yu
Sen Zhao
FedMLAI4CE
259
6,261
0
10 Dec 2019
Overcoming Forgetting in Federated Learning on Non-IID Data
Overcoming Forgetting in Federated Learning on Non-IID Data
N. Shoham
Tomer Avidor
Aviv Keren
Nadav Tal-Israel
Daniel Benditkis
Liron Mor Yosef
Itai Zeitak
CLLFedML
130
226
0
17 Oct 2019
The Non-IID Data Quagmire of Decentralized Machine Learning
The Non-IID Data Quagmire of Decentralized Machine Learning
Kevin Hsieh
Amar Phanishayee
O. Mutlu
Phillip B. Gibbons
161
568
0
01 Oct 2019
Measuring the Effects of Non-Identical Data Distribution for Federated
  Visual Classification
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
T. Hsu
Qi
Matthew Brown
FedML
143
1,150
0
13 Sep 2019
Applied Federated Learning: Improving Google Keyboard Query Suggestions
Applied Federated Learning: Improving Google Keyboard Query Suggestions
Timothy Yang
Galen Andrew
Hubert Eichner
Haicheng Sun
Wei Li
Nicholas Kong
Daniel Ramage
F. Beaufays
FedML
87
626
0
07 Dec 2018
LEAF: A Benchmark for Federated Settings
LEAF: A Benchmark for Federated Settings
S. Caldas
Sai Meher Karthik Duddu
Peter Wu
Tian Li
Jakub Konecný
H. B. McMahan
Virginia Smith
Ameet Talwalkar
FedML
149
1,422
0
03 Dec 2018
Parallel Restarted SGD with Faster Convergence and Less Communication:
  Demystifying Why Model Averaging Works for Deep Learning
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning
Hao Yu
Sen Yang
Shenghuo Zhu
MoMeFedML
75
608
0
17 Jul 2018
MobileNetV2: Inverted Residuals and Linear Bottlenecks
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Mark Sandler
Andrew G. Howard
Menglong Zhu
A. Zhmoginov
Liang-Chieh Chen
184
19,316
0
13 Jan 2018
Overcoming catastrophic forgetting in neural networks
Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick
Razvan Pascanu
Neil C. Rabinowitz
J. Veness
Guillaume Desjardins
...
A. Grabska-Barwinska
Demis Hassabis
Claudia Clopath
D. Kumaran
R. Hadsell
CLL
369
7,518
0
02 Dec 2016
Communication-Efficient Learning of Deep Networks from Decentralized
  Data
Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
FedML
406
17,486
0
17 Feb 2016
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