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On the Optimality of Averaging in Distributed Statistical Learning

On the Optimality of Averaging in Distributed Statistical Learning

10 July 2014
Jonathan D. Rosenblatt
B. Nadler
    FedML
ArXivPDFHTML

Papers citing "On the Optimality of Averaging in Distributed Statistical Learning"

15 / 15 papers shown
Title
Copula Approximate Bayesian Computation Using Distribution Random
  Forests
Copula Approximate Bayesian Computation Using Distribution Random Forests
G. Karabatsos
42
1
0
28 Feb 2024
A review of distributed statistical inference
A review of distributed statistical inference
Yuan Gao
Weidong Liu
Hansheng Wang
Xiaozhou Wang
Yibo Yan
Riquan Zhang
16
42
0
13 Apr 2023
Distributed Sparse Linear Regression under Communication Constraints
Distributed Sparse Linear Regression under Communication Constraints
R. Fonseca
B. Nadler
FedML
19
2
0
09 Jan 2023
Communication-efficient Distributed Newton-like Optimization with
  Gradients and M-estimators
Communication-efficient Distributed Newton-like Optimization with Gradients and M-estimators
Ziyan Yin
32
0
0
13 Jul 2022
Distributed Sparse Regression via Penalization
Distributed Sparse Regression via Penalization
Yao Ji
G. Scutari
Ying Sun
Harsha Honnappa
22
5
0
12 Nov 2021
Federated Composite Optimization
Federated Composite Optimization
Honglin Yuan
Manzil Zaheer
Sashank J. Reddi
FedML
32
58
0
17 Nov 2020
Distributed function estimation: adaptation using minimal communication
Distributed function estimation: adaptation using minimal communication
Botond Szabó
Harry Van Zanten
27
13
0
28 Mar 2020
Is Local SGD Better than Minibatch SGD?
Is Local SGD Better than Minibatch SGD?
Blake E. Woodworth
Kumar Kshitij Patel
Sebastian U. Stich
Zhen Dai
Brian Bullins
H. B. McMahan
Ohad Shamir
Nathan Srebro
FedML
34
253
0
18 Feb 2020
Communication-Efficient Accurate Statistical Estimation
Communication-Efficient Accurate Statistical Estimation
Jianqing Fan
Yongyi Guo
Kaizheng Wang
19
110
0
12 Jun 2019
Effective Parallelisation for Machine Learning
Effective Parallelisation for Machine Learning
Michael Kamp
Mario Boley
Olana Missura
Thomas Gärtner
11
12
0
08 Oct 2018
Parallelizing Stochastic Gradient Descent for Least Squares Regression:
  mini-batching, averaging, and model misspecification
Parallelizing Stochastic Gradient Descent for Least Squares Regression: mini-batching, averaging, and model misspecification
Prateek Jain
Sham Kakade
Rahul Kidambi
Praneeth Netrapalli
Aaron Sidford
MoMe
21
36
0
12 Oct 2016
Bootstrap Model Aggregation for Distributed Statistical Learning
Bootstrap Model Aggregation for Distributed Statistical Learning
J. Han
Qiang Liu
FedML
18
9
0
04 Jul 2016
Efficient Distributed Learning with Sparsity
Efficient Distributed Learning with Sparsity
Jialei Wang
Mladen Kolar
Nathan Srebro
Tong Zhang
FedML
24
151
0
25 May 2016
A Distributed One-Step Estimator
A Distributed One-Step Estimator
Cheng Huang
X. Huo
FedML
16
80
0
04 Nov 2015
Communication-efficient sparse regression: a one-shot approach
Communication-efficient sparse regression: a one-shot approach
J. Lee
Yuekai Sun
Qiang Liu
Jonathan E. Taylor
43
65
0
14 Mar 2015
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