ResearchTrend.AI
IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method

IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method

Yossi Arjevani
Joan Bruna
Bugra Can
Mert Gurbuzbalaban
Stefanie Jegelka
Hongzhou Lin
ArXivPDFHTML

Papers citing "IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method"

5 / 5 papers shown
Title
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
Sulaiman A. Alghunaim
Kun Yuan
Ali H. Sayed
49
62
0
20 May 2019
A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks
A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks
César A. Uribe
Soomin Lee
Alexander Gasnikov
A. Nedić
38
137
0
03 Sep 2018
Federated Learning: Strategies for Improving Communication Efficiency
Federated Learning: Strategies for Improving Communication Efficiency
Jakub Konecný
H. B. McMahan
Felix X. Yu
Peter Richtárik
A. Suresh
Dave Bacon
FedML
271
4,620
0
18 Oct 2016
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks
Julien Mairal
SSL
54
130
0
20 May 2016
Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization
Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization
Mark Schmidt
Nicolas Le Roux
Francis R. Bach
159
582
0
12 Sep 2011

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.