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Parallel Training of Deep Networks with Local Updates
v1v2 (latest)

Parallel Training of Deep Networks with Local Updates

7 December 2020
Michael Laskin
Luke Metz
Seth Nabarrao
Mark Saroufim
Badreddine Noune
Carlo Luschi
Jascha Narain Sohl-Dickstein
Pieter Abbeel
    FedML
ArXiv (abs)PDFHTMLGithub (35505★)

Papers citing "Parallel Training of Deep Networks with Local Updates"

16 / 16 papers shown
On Advancements of the Forward-Forward Algorithm
On Advancements of the Forward-Forward Algorithm
Mauricio Ortiz Torres
Markus Lange
Arne P. Raulf
374
2
0
30 Apr 2025
Momentum Auxiliary Network for Supervised Local Learning
Momentum Auxiliary Network for Supervised Local Learning
Junhao Su
Xiuyuan Guo
Feiyu Zhu
Chenghao He
Xiaojie Xu
Dongzhi Guan
Chenyang Si
548
7
0
08 Jul 2024
Going Forward-Forward in Distributed Deep Learning
Going Forward-Forward in Distributed Deep Learning
Ege Aktemur
Ege Zorlutuna
Kaan Bilgili
Tacettin Emre Bok
Berrin Yanikoglu
Suha Orhun Mutluergil
FedML
253
1
0
30 Mar 2024
Scaling Supervised Local Learning with Augmented Auxiliary Networks
Scaling Supervised Local Learning with Augmented Auxiliary Networks
Chenxiang Ma
Jibin Wu
Chenyang Si
Kay Chen Tan
263
8
0
27 Feb 2024
Speed Up Federated Learning in Heterogeneous Environment: A Dynamic
  Tiering Approach
Speed Up Federated Learning in Heterogeneous Environment: A Dynamic Tiering Approach
Seyed Mahmoud Sajjadi Mohammadabadi
Syed Zawad
Feng Yan
Lei Yang
FedML
281
8
0
09 Dec 2023
The Trifecta: Three simple techniques for training deeper
  Forward-Forward networks
The Trifecta: Three simple techniques for training deeper Forward-Forward networks
Thomas Dooms
Ing Jyh Tsang
José Oramas
295
11
0
29 Nov 2023
Local Learning with Neuron Groups
Local Learning with Neuron Groups
Adeetya Patel
Michael Eickenberg
Eugene Belilovsky
200
6
0
18 Jan 2023
Scaling Laws Beyond Backpropagation
Scaling Laws Beyond Backpropagation
Matthew J. Filipovich
Alessandro Cappelli
Daniel Hesslow
Julien Launay
294
5
0
26 Oct 2022
Scaling Forward Gradient With Local Losses
Scaling Forward Gradient With Local LossesInternational Conference on Learning Representations (ICLR), 2022
Mengye Ren
Simon Kornblith
Renjie Liao
Geoffrey E. Hinton
614
73
0
07 Oct 2022
Locally Supervised Learning with Periodic Global Guidance
Locally Supervised Learning with Periodic Global Guidance
Hasnain Irshad Bhatti
Jaekyun Moon
168
1
0
01 Aug 2022
Efficient Attribute Unlearning: Towards Selective Removal of Input
  Attributes from Feature Representations
Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations
Tao Guo
Song Guo
Jiewei Zhang
Wenchao Xu
Junxiao Wang
MU
324
27
0
27 Feb 2022
AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep
  Learning
AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning
Ayush Chopra
Surya Kant Sahu
Abhishek Singh
Abhinav Java
Praneeth Vepakomma
Vivek Sharma
Ramesh Raskar
243
32
0
02 Dec 2021
Training Spiking Neural Networks Using Lessons From Deep Learning
Training Spiking Neural Networks Using Lessons From Deep LearningProceedings of the IEEE (Proc. IEEE), 2021
Nhan Duy Truong
Max Ward
Emre Neftci
Xinxin Wang
Gregor Lenz
Girish Dwivedi
Bennamoun
Doo Seok Jeong
Wei D. Lu
680
773
0
27 Sep 2021
Feature Alignment as a Generative Process
Feature Alignment as a Generative Process
T. S. Farias
Jonas Maziero
DiffMBDL
314
1
0
23 Jun 2021
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous
  Distributed Learning
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning
Eugene Belilovsky
Louis Leconte
Lucas Caccia
Michael Eickenberg
Edouard Oyallon
240
9
0
11 Jun 2021
Interlocking Backpropagation: Improving depthwise model-parallelism
Interlocking Backpropagation: Improving depthwise model-parallelismJournal of machine learning research (JMLR), 2020
Aidan Gomez
Oscar Key
Kuba Perlin
Stephen Gou
Nick Frosst
J. Dean
Y. Gal
328
23
0
08 Oct 2020
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