Adding vs. Averaging in Distributed Primal-Dual Optimization

12 February 2015

Papers citing "Adding vs. Averaging in Distributed Primal-Dual Optimization"

29 / 29 papers shown

Title
On ADMM in Heterogeneous Federated Learning: Personalization, Robustness, and Fairness Shengkun Zhu Jinshan Zeng Sheng Wang Yuan Sun Xiaodong Li Yuan Yao Zhiyong Peng 52 0 0 23 Jul 2024
Heterogeneous Federated Learning: State-of-the-art and Research Challenges Mang Ye Xiuwen Fang Bo Du PongChi Yuen Dacheng Tao FedML AAML 39 244 0 20 Jul 2023
On the Optimal Batch Size for Byzantine-Robust Distributed Learning Yi-Rui Yang Chang-Wei Shi Wu-Jun Li FedML AAML 21 0 0 23 May 2023
Gradient-Leakage Resilient Federated Learning Wenqi Wei Ling Liu Yanzhao Wu Gong Su Arun Iyengar FedML 19 81 0 02 Jul 2021
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks Chaoyang He Emir Ceyani Keshav Balasubramanian M. Annavaram Salman Avestimehr FedML 25 50 0 04 Jun 2021
Towards Demystifying Serverless Machine Learning Training Jiawei Jiang Shaoduo Gan Yue Liu Fanlin Wang Gustavo Alonso Ana Klimovic Ankit Singla Wentao Wu Ce Zhang 19 121 0 17 May 2021
Toward Multiple Federated Learning Services Resource Sharing in Mobile Edge Networks Minh N. H. Nguyen N. H. Tran Y. Tun Zhu Han Choong Seon Hong FedML 24 49 0 25 Nov 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 32 0 0 26 Aug 2020
Buffered Asynchronous SGD for Byzantine Learning Yi-Rui Yang Wu-Jun Li FedML 29 5 0 02 Mar 2020
Faster On-Device Training Using New Federated Momentum Algorithm Zhouyuan Huo Qian Yang Bin Gu Heng-Chiao Huang FedML 22 47 0 06 Feb 2020
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling Mojmír Mutný Michal Derezinski Andreas Krause 35 20 0 25 Oct 2019
Variational Federated Multi-Task Learning Luca Corinzia Ami Beuret J. M. Buhmann FedML 27 159 0 14 Jun 2019
99% of Distributed Optimization is a Waste of Time: The Issue and How to Fix it Konstantin Mishchenko Filip Hanzely Peter Richtárik 16 13 0 27 Jan 2019
Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning Tribhuvanesh Orekondy Seong Joon Oh Yang Zhang Bernt Schiele Mario Fritz PICV FedML 357 37 0 15 May 2018
Improved asynchronous parallel optimization analysis for stochastic incremental methods Rémi Leblond Fabian Pedregosa Simon Lacoste-Julien 16 70 0 11 Jan 2018
GIANT: Globally Improved Approximate Newton Method for Distributed Optimization Shusen Wang Farbod Roosta-Khorasani Peng Xu Michael W. Mahoney 33 127 0 11 Sep 2017
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 15 1,776 0 30 May 2017
Distributed Dual Coordinate Ascent in General Tree Networks and Communication Network Effect on Synchronous Machine Learning Myung Cho Lifeng Lai Weiyu Xu 14 1 0 14 Mar 2017
Optimization for Large-Scale Machine Learning with Distributed Features and Observations A. Nathan Diego Klabjan 30 13 0 31 Oct 2016
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 36 4,588 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 51 1,876 0 08 Oct 2016
AIDE: Fast and Communication Efficient Distributed Optimization Sashank J. Reddi Jakub Konecný Peter Richtárik Barnabás Póczós Alex Smola 16 150 0 24 Aug 2016
ASAGA: Asynchronous Parallel SAGA Rémi Leblond Fabian Pedregosa Simon Lacoste-Julien AI4TS 23 101 0 15 Jun 2016
A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization Shun Zheng Jialei Wang Fen Xia Wenyuan Xu Tong Zhang 18 22 0 13 Apr 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 24 16,996 0 17 Feb 2016
SCOPE: Scalable Composite Optimization for Learning on Spark Shen-Yi Zhao Ru Xiang Yinghuan Shi Peng Gao Wu-Jun Li 16 16 0 30 Jan 2016
L1-Regularized Distributed Optimization: A Communication-Efficient Primal-Dual Framework Virginia Smith Simone Forte Michael I. Jordan Martin Jaggi 28 28 0 13 Dec 2015
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections C. Heinze Brian McWilliams N. Meinshausen 31 37 0 08 Jun 2015
Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting Jakub Konecný Jie Liu Peter Richtárik Martin Takáč ODL 25 273 0 16 Apr 2015