Distributed Learning in Non-Convex Environments -- Part I: Agreement at a Linear Rate

3 July 2019

Papers citing "Distributed Learning in Non-Convex Environments -- Part I: Agreement at a Linear Rate"

28 / 28 papers shown

Title
Deep-Relative-Trust-Based Diffusion for Decentralized Deep Learning Muyun Li Aaron Fainman Stefan Vlaski 65 0 0 06 Jan 2025
Attribute Inference Attacks for Federated Regression Tasks Francesco Diana Othmane Marfoq Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML 559 1 0 19 Nov 2024
Decentralized Adversarial Training over Graphs Ying Cao Elsa Rizk Stefan Vlaski Ali H. Sayed AAML 114 1 0 23 Mar 2023
Second-Order Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization Stefan Vlaski Ali H. Sayed 68 5 0 31 Mar 2020
Distributed Learning in Non-Convex Environments -- Part II: Polynomial Escape from Saddle-Points Stefan Vlaski Ali H. Sayed 63 53 0 03 Jul 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization Rong Ge Zhize Li Weiyao Wang Xiang Wang 49 34 0 01 May 2019
Distributed stochastic optimization with gradient tracking over strongly-connected networks Ran Xin Anit Kumar Sahu U. Khan S. Kar 70 112 0 18 Mar 2019
Annealing for Distributed Global Optimization Brian Swenson S. Kar H. Vincent Poor J. M. F. Moura 70 30 0 18 Mar 2019
On Nonconvex Optimization for Machine Learning: Gradients, Stochasticity, and Saddle Points Chi Jin Praneeth Netrapalli Rong Ge Sham Kakade Michael I. Jordan 79 61 0 13 Feb 2019
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points Cong Fang Zhouchen Lin Tong Zhang 71 104 0 01 Feb 2019
Second-order Guarantees of Distributed Gradient Algorithms Amir Daneshmand G. Scutari Vyacheslav Kungurtsev 74 59 0 23 Sep 2018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator Cong Fang C. J. Li Zhouchen Lin Tong Zhang 89 579 0 04 Jul 2018
Escaping Saddles with Stochastic Gradients Hadi Daneshmand Jonas Köhler Aurelien Lucchi Thomas Hofmann 63 162 0 15 Mar 2018
Non-convex Optimization for Machine Learning Prateek Jain Purushottam Kar 158 486 0 21 Dec 2017
Neon2: Finding Local Minima via First-Order Oracles Zeyuan Allen-Zhu Yuanzhi Li 64 131 0 17 Nov 2017
Natasha 2: Faster Non-Convex Optimization Than SGD Zeyuan Allen-Zhu ODL 79 246 0 29 Aug 2017
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 Ji Liu 50 1,228 0 25 May 2017
Performance Limits of Stochastic Sub-Gradient Learning, Part II: Multi-Agent Case Bicheng Ying Ali H. Sayed 23 17 0 20 Apr 2017
How to Escape Saddle Points Efficiently Chi Jin Rong Ge Praneeth Netrapalli Sham Kakade Michael I. Jordan ODL 224 836 0 02 Mar 2017
Stochastic Variance Reduction for Nonconvex Optimization Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 96 602 0 19 Mar 2016
NEXT: In-Network Nonconvex Optimization P. Lorenzo G. Scutari 103 508 0 01 Feb 2016
Proximal Multitask Learning over Networks with Sparsity-inducing Coregularization Roula Nassif C. Richard A. Ferrari Ali H. Sayed 58 58 0 04 Sep 2015
Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition Rong Ge Furong Huang Chi Jin Yang Yuan 137 1,058 0 06 Mar 2015
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 261 1,198 0 30 Nov 2014
On the Learning Behavior of Adaptive Networks - Part I: Transient Analysis Jianshu Chen Ali H. Sayed 91 132 0 29 Dec 2013
On the Learning Behavior of Adaptive Networks - Part II: Performance Analysis Jianshu Chen Ali H. Sayed 87 83 0 29 Dec 2013
Asynchronous Adaptation and Learning over Networks - Part II: Performance Analysis Xiaochuan Zhao Ali H. Sayed 83 43 0 19 Dec 2013
Adaptive Penalty-Based Distributed Stochastic Convex Optimization Zaid J. Towfic Ali H. Sayed 74 89 0 16 Dec 2013