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GIANT: Globally Improved Approximate Newton Method for Distributed
  Optimization

GIANT: Globally Improved Approximate Newton Method for Distributed Optimization

11 September 2017
Shusen Wang
Farbod Roosta-Khorasani
Peng Xu
Michael W. Mahoney
ArXivPDFHTML

Papers citing "GIANT: Globally Improved Approximate Newton Method for Distributed Optimization"

24 / 24 papers shown
Title
Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors
  Quantization
Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization
Nicolò Dal Fabbro
M. Rossi
Luca Schenato
S. Dey
21
0
0
18 May 2023
Network-GIANT: Fully distributed Newton-type optimization via harmonic
  Hessian consensus
Network-GIANT: Fully distributed Newton-type optimization via harmonic Hessian consensus
A. Maritan
Ganesh Sharma
Luca Schenato
S. Dey
25
2
0
13 May 2023
FedSSO: A Federated Server-Side Second-Order Optimization Algorithm
FedSSO: A Federated Server-Side Second-Order Optimization Algorithm
Xinteng Ma
Renyi Bao
Jinpeng Jiang
Yang Liu
Arthur Jiang
Junhua Yan
Xin Liu
Zhisong Pan
FedML
32
6
0
20 Jun 2022
Over-the-Air Federated Learning via Second-Order Optimization
Over-the-Air Federated Learning via Second-Order Optimization
Peng Yang
Yuning Jiang
Ting Wang
Yong Zhou
Yuanming Shi
Colin N. Jones
45
28
0
29 Mar 2022
FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling
  and Correction
FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction
Liang Gao
H. Fu
Li Li
Yingwen Chen
Minghua Xu
Chengzhong Xu
FedML
21
242
0
22 Mar 2022
SHED: A Newton-type algorithm for federated learning based on
  incremental Hessian eigenvector sharing
SHED: A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing
Nicolò Dal Fabbro
S. Dey
M. Rossi
Luca Schenato
FedML
29
14
0
11 Feb 2022
Communication-Efficient Stochastic Zeroth-Order Optimization for
  Federated Learning
Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learning
Wenzhi Fang
Ziyi Yu
Yuning Jiang
Yuanming Shi
Colin N. Jones
Yong Zhou
FedML
78
56
0
24 Jan 2022
Basis Matters: Better Communication-Efficient Second Order Methods for
  Federated Learning
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning
Xun Qian
Rustem Islamov
M. Safaryan
Peter Richtárik
FedML
19
23
0
02 Nov 2021
Resource-constrained Federated Edge Learning with Heterogeneous Data:
  Formulation and Analysis
Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis
Yi Liu
Yuanshao Zhu
James J. Q. Yu
FedML
27
28
0
14 Oct 2021
A Stochastic Newton Algorithm for Distributed Convex Optimization
A Stochastic Newton Algorithm for Distributed Convex Optimization
Brian Bullins
Kumar Kshitij Patel
Ohad Shamir
Nathan Srebro
Blake E. Woodworth
26
15
0
07 Oct 2021
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton
  Update
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update
Michal Derezinski
Jonathan Lacotte
Mert Pilanci
Michael W. Mahoney
32
26
0
15 Jul 2021
FedNL: Making Newton-Type Methods Applicable to Federated Learning
FedNL: Making Newton-Type Methods Applicable to Federated Learning
M. Safaryan
Rustem Islamov
Xun Qian
Peter Richtárik
FedML
25
77
0
05 Jun 2021
Distributed Second Order Methods with Fast Rates and Compressed
  Communication
Distributed Second Order Methods with Fast Rates and Compressed Communication
Rustem Islamov
Xun Qian
Peter Richtárik
29
51
0
14 Feb 2021
Newton Method over Networks is Fast up to the Statistical Precision
Newton Method over Networks is Fast up to the Statistical Precision
Amir Daneshmand
G. Scutari
Pavel Dvurechensky
Alexander Gasnikov
22
21
0
12 Feb 2021
DONE: Distributed Approximate Newton-type Method for Federated Edge
  Learning
DONE: Distributed Approximate Newton-type Method for Federated Edge Learning
Canh T. Dinh
N. H. Tran
Tuan Dung Nguyen
Wei Bao
A. R. Balef
B. Zhou
Albert Y. Zomaya
FedML
18
15
0
10 Dec 2020
Sparse sketches with small inversion bias
Sparse sketches with small inversion bias
Michal Derezinski
Zhenyu Liao
Edgar Dobriban
Michael W. Mahoney
17
21
0
21 Nov 2020
Artificial Intelligence for UAV-enabled Wireless Networks: A Survey
Artificial Intelligence for UAV-enabled Wireless Networks: A Survey
Mohamed-Amine Lahmeri
Mustafa A. Kishk
Mohamed-Slim Alouini
18
102
0
24 Sep 2020
Precise expressions for random projections: Low-rank approximation and
  randomized Newton
Precise expressions for random projections: Low-rank approximation and randomized Newton
Michal Derezinski
Feynman T. Liang
Zhenyu A. Liao
Michael W. Mahoney
24
23
0
18 Jun 2020
Communication-Efficient Edge AI: Algorithms and Systems
Communication-Efficient Edge AI: Algorithms and Systems
Yuanming Shi
Kai Yang
Tao Jiang
Jun Zhang
Khaled B. Letaief
GNN
17
326
0
22 Feb 2020
Intermittent Pulling with Local Compensation for Communication-Efficient
  Federated Learning
Intermittent Pulling with Local Compensation for Communication-Efficient Federated Learning
Haozhao Wang
Zhihao Qu
Song Guo
Xin Gao
Ruixuan Li
Baoliu Ye
FedML
6
8
0
22 Jan 2020
Communication-Efficient Local Decentralized SGD Methods
Communication-Efficient Local Decentralized SGD Methods
Xiang Li
Wenhao Yang
Shusen Wang
Zhihua Zhang
22
53
0
21 Oct 2019
On the Convergence of FedAvg on Non-IID Data
On the Convergence of FedAvg on Non-IID Data
Xiang Li
Kaixuan Huang
Wenhao Yang
Shusen Wang
Zhihua Zhang
FedML
38
2,278
0
04 Jul 2019
Communication-Efficient Accurate Statistical Estimation
Communication-Efficient Accurate Statistical Estimation
Jianqing Fan
Yongyi Guo
Kaizheng Wang
11
110
0
12 Jun 2019
A Distributed Second-Order Algorithm You Can Trust
A Distributed Second-Order Algorithm You Can Trust
Celestine Mendler-Dünner
Aurélien Lucchi
Matilde Gargiani
An Bian
Thomas Hofmann
Martin Jaggi
16
32
0
20 Jun 2018
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