A Decentralized Second-Order Method with Exact Linear Convergence Rate
for Consensus Optimization

A Decentralized Second-Order Method with Exact Linear Convergence Rate for Consensus Optimization

1 February 2016

Alejandro Ribeiro

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Papers citing "A Decentralized Second-Order Method with Exact Linear Convergence Rate for Consensus Optimization"

18 / 18 papers shown

Title
Variance-Reduced Stochastic Quasi-Newton Methods for Decentralized Learning: Part I Jiaojiao Zhang Huikang Liu Anthony Man-Cho So Qing Ling 90 15 0 19 Jan 2022
GT-STORM: Taming Sample, Communication, and Memory Complexities in Decentralized Non-Convex Learning Xin Zhang Jia Liu Zhengyuan Zhu Elizabeth S. Bentley 84 14 0 04 May 2021
A Survey of Distributed Optimization Methods for Multi-Robot Systems Trevor Halsted O. Shorinwa Javier Yu Mac Schwager 103 41 0 23 Mar 2021
Newton Method over Networks is Fast up to the Statistical Precision Amir Daneshmand G. Scutari Pavel Dvurechensky Alexander Gasnikov 60 22 0 12 Feb 2021
Distributed Adaptive Newton Methods with Global Superlinear Convergence Jiaqi Zhang Keyou You Tamer Basar 36 22 0 18 Feb 2020
Communication-Censored Linearized ADMM for Decentralized Consensus Optimization Weiyu Li Yaohua Liu Z. Tian Qing Ling 58 22 0 15 Sep 2019
BRIDGE: Byzantine-resilient Decentralized Gradient Descent Cheng Fang Zhixiong Yang W. Bajwa 80 101 0 21 Aug 2019
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization Sulaiman A. Alghunaim Kun Yuan Ali H. Sayed 82 62 0 20 May 2019
Distributed Nesterov gradient methods over arbitrary graphs Ran Xin D. Jakovetić U. Khan 55 58 0 21 Jan 2019
Push-Pull Gradient Methods for Distributed Optimization in Networks Shi Pu Wei Shi Jinming Xu A. Nedić 86 322 0 15 Oct 2018
Distributed Nonconvex Constrained Optimization over Time-Varying Digraphs G. Scutari Ying Sun 97 176 0 04 Sep 2018
Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization G. Scutari Ying Sun 100 63 0 17 May 2018
A Push-Pull Gradient Method for Distributed Optimization in Networks Shi Pu Wei Shi Jinming Xu A. Nedić 72 98 0 20 Mar 2018
ByRDiE: Byzantine-resilient distributed coordinate descent for decentralized learning Zhixiong Yang W. Bajwa OOD 81 134 0 28 Aug 2017
Stochastic L-BFGS: Improved Convergence Rates and Practical Acceleration Strategies Renbo Zhao W. Haskell Vincent Y. F. Tan 53 29 0 01 Apr 2017
Optimal algorithms for smooth and strongly convex distributed optimization in networks Kevin Scaman Francis R. Bach Sébastien Bubeck Y. Lee Laurent Massoulié 86 331 0 28 Feb 2017
Communication-Efficient Algorithms for Decentralized and Stochastic Optimization Guanghui Lan Soomin Lee Yi Zhou 113 219 0 14 Jan 2017
A Decentralized Quasi-Newton Method for Dual Formulations of Consensus Optimization Mark Eisen Aryan Mokhtari Alejandro Ribeiro 52 14 0 23 Mar 2016