Server-Side Local Gradient Averaging and Learning Rate Acceleration for Scalable Split Learning

11 December 2021

Papers citing "Server-Side Local Gradient Averaging and Learning Rate Acceleration for Scalable Split Learning"

22 / 22 papers shown

Title
Faithful Edge Federated Learning: Scalability and Privacy Meng Zhang Ermin Wei R. Berry FedML 42 44 0 30 Jun 2021
Revisiting Locally Supervised Learning: an Alternative to End-to-end Training Yulin Wang Zanlin Ni Shiji Song Le Yang Gao Huang 63 84 0 26 Jan 2021
A Framework For Contrastive Self-Supervised Learning And Designing A New Approach William Falcon Kyunghyun Cho SSL 67 104 0 31 Aug 2020
Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications Jihong Park S. Samarakoon Anis Elgabli Joongheon Kim M. Bennis Seong-Lyun Kim Mérouane Debbah 57 163 0 06 Aug 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 680 41,736 0 28 May 2020
SplitFed: When Federated Learning Meets Split Learning Chandra Thapa Pathum Chamikara Mahawaga Arachchige S. Çamtepe Lichao Sun FedML 85 575 0 25 Apr 2020
Inverting Gradients -- How easy is it to break privacy in federated learning? Jonas Geiping Hartmut Bauermeister Hannah Dröge Michael Moeller FedML 96 1,222 0 31 Mar 2020
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 529 24,351 0 26 Jul 2019
Wireless Network Intelligence at the Edge Jihong Park S. Samarakoon M. Bennis Mérouane Debbah 93 521 0 07 Dec 2018
Split learning for health: Distributed deep learning without sharing raw patient data Praneeth Vepakomma O. Gupta Tristan Swedish Ramesh Raskar FedML 118 702 0 03 Dec 2018
Distributed learning of deep neural network over multiple agents O. Gupta Ramesh Raskar FedML OOD 54 603 0 14 Oct 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.6K 94,511 0 11 Oct 2018
The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches Md. Zahangir Alom T. Taha C. Yakopcic Stefan Westberg P. Sidike Mst Shamima Nasrin B. Van Essen A. Awwal V. Asari VLM 71 881 0 03 Mar 2018
Don't Decay the Learning Rate, Increase the Batch Size Samuel L. Smith Pieter-Jan Kindermans Chris Ying Quoc V. Le ODL 97 994 0 01 Nov 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 254 8,856 0 25 Aug 2017
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour Priya Goyal Piotr Dollár Ross B. Girshick P. Noordhuis Lukasz Wesolowski Aapo Kyrola Andrew Tulloch Yangqing Jia Kaiming He 3DH 120 3,675 0 08 Jun 2017
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 723 36,708 0 25 Aug 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.0K 193,426 0 10 Dec 2015
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 787 27,303 0 02 Dec 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.5K 149,842 0 22 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.5K 100,213 0 04 Sep 2014
One weird trick for parallelizing convolutional neural networks A. Krizhevsky GNN 88 1,298 0 23 Apr 2014