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Communication compression has become a key strategy to speed up distributed optimization.
Deepsqueeze: Decentralization meets error-compensated compression
Hanlin Tang, Xiangru Lian, Shuang Qiu, Lei Yuan, Ce Zhang, Tong Zhang, and Ji Liu · 1907
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Distributed asynchronous deterministic and stochastic gradient optimization algorithms
John Tsitsiklis, Dimitri Bertsekas, and Michael Athans · 1986
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Fast linear iterations for distributed averaging
Lin Xiao and Stephen Boyd · 2004
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Distributed subgradient methods for multi-agent optimization
Angelia Nedic and Asuman Ozdaglar · 2009
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Gossip consensus algorithms via quantized communication
Ruggero Carli, Fabio Fagnani, Paolo Frasca, and Sandro Zampieri · 2010
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D-ADMM: A communication-efficient distributed algorithm for separable optimization
Joao FC Mota, Joao MF Xavier, Pedro MQ Aguiar, and Markus Püschel · 2013
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Introductory lectures on convex optimization: A basic course , volume 87
Yurii Nesterov · 2013
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1-bit stochastic gradient descent and application to data-parallel distributed training of speech DNNs
Frank Seide, Hao Fu, Jasha Droppo, Gang Li, and Dong Yu · 2014
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DLM: Decentralized linearized alternating direction method of multipliers
Qing Ling, Wei Shi, Gang Wu, and Alejandro Ribeiro · 2015
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EXTRA: An exact first-order algorithm for decentralized consensus optimization
Wei Shi, Qing Ling, Gang Wu, and Wotao Yin · 2015
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On the convergence of decentralized gradient descent
Kun Yuan, Qing Ling, and Wotao Yin · 2016
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QSGD: Communication-efficient sgd via gradient quantization and encoding
Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, and Milan Vojnovic · 2017
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Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent
Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, and Ji Liu · 2017
Cited alongside, same era.
Achieving geometric convergence for distributed optimization over time-varying graphs
Angelia Nedic, Alex Olshevsky, and Wei Shi · 2017
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SIGNSGD: compressed optimisation for non-convex problems
Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, and Animashree Anandkumar · 2018
Cited alongside, same era.
Sparsified SGD with memory
On linear convergence of two decentralized algorithms
Yao Li and Ming Yan · 2019
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A decentralized proximal-gradient method with network independent step-sizes and separated convergence rates
Zhi Li, Wei Shi, and Ming Yan · 2019
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Distributed learning with compressed gradient differences
Konstantin Mishchenko, Eduard Gorbunov, Martin Takáč, and Peter Richtárik · 2019
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Decentralized deep learning with arbitrary communication compression
Anastasia Koloskova, Tao Lin, Sebastian U Stich, and Martin Jaggi · 2020
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A double residual compression algorithm for efficient distributed learning
Xiaorui Liu, Yao Li, Jiliang Tang, and Ming Yan · 2020
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Sebastian U. Stich, Jean-Baptiste Cordonnier, and Martin Jaggi · 2018
Cited alongside, same era.
Error compensated quantized SGD and its applications to large-scale distributed optimization
Jiaxiang Wu, Weidong Huang, Junzhou Huang, and Tong Zhang · 2018
Cited alongside, same era.
Exact diffusion for distributed optimization and learning—part i: Algorithm development
Kun Yuan, Bicheng Ying, Xiaochuan Zhao, and Ali H Sayed · 2018
Cited alongside, same era.
Error feedback fixes SignSGD and other gradient compression schemes
Sai Praneeth Karimireddy, Quentin Rebjock, Sebastian Urban Stich, and Martin Jaggi · 2019
Cited alongside, same era.
Decentralized stochastic optimization and gossip algorithms with compressed communication
Anastasia Koloskova, Sebastian U. Stich, and Martin Jaggi · 2019
Cited alongside, same era.
An exact quantized decentralized gradient descent algorithm
Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani, and Ramtin Pedarsani
Cited in the paper.
Robust and communication-efficient collaborative learning
Amirhossein Reisizadeh, Hossein Taheri, Aryan Mokhtari, Hamed Hassani, and Ramtin Pedarsani
Cited in the paper.
Moniqua: Modulo quantized communication in decentralized SGD
Yucheng Lu and Christopher De Sa · 2020
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On maintaining linear convergence of distributed learning and optimization under limited communication
Sindri Magnússon, Hossein Shokri-Ghadikolaei, and Na Li · 2020
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Distributed stochastic gradient tracking methods
Shi Pu and Angelia Nedić · 2020
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Accelerated primal-dual algorithms for distributed smooth convex optimization over networks
Jinming Xu, Ye Tian, Ying Sun, and Gesualdo Scutari · 2020
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Can primal methods outperform primal-dual methods in decentralized dynamic optimization?
Kun Yuan, Wei Xu, and Qing Ling · 2020
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