CoCoA: A General Framework for Communication-Efficient Distributed Optimization

7 November 2016

Papers citing "CoCoA: A General Framework for Communication-Efficient Distributed Optimization"

50 / 52 papers shown

Title
Communication-Efficient, 2D Parallel Stochastic Gradient Descent for Distributed-Memory Optimization Aditya Devarakonda Ramakrishnan Kannan FedML 37 0 0 13 Jan 2025
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
Flattened one-bit stochastic gradient descent: compressed distributed optimization with controlled variance A. Stollenwerk Laurent Jacques FedML 28 0 0 17 May 2024
Analysis of Total Variation Minimization for Clustered Federated Learning Alexander Jung 16 2 0 10 Mar 2024
Federated Learning for Sparse Principal Component Analysis Sin Cheng Ciou Pin-Jui Chen Elvin Y. Tseng Yuh-Jye Lee FedML 26 0 0 15 Nov 2023
Continual Learning with Distributed Optimization: Does CoCoA Forget? Martin Hellkvist Ayça Özçelikkale Anders Ahlén CLL OOD 27 1 0 30 Nov 2022
FeDXL: Provable Federated Learning for Deep X-Risk Optimization Zhishuai Guo Rong Jin Jiebo Luo Tianbao Yang FedML 47 8 0 26 Oct 2022
Recovery Guarantees for Distributed-OMP Chen Amiraz Robert Krauthgamer B. Nadler 26 0 0 15 Sep 2022
Cerberus: Exploring Federated Prediction of Security Events Mohammad Naseri Yufei Han Enrico Mariconti Yun Shen Gianluca Stringhini Emiliano De Cristofaro FedML 45 14 0 07 Sep 2022
Flexible Vertical Federated Learning with Heterogeneous Parties Timothy Castiglia Shiqiang Wang S. Patterson FedML 42 34 0 26 Aug 2022
FedGiA: An Efficient Hybrid Algorithm for Federated Learning Shenglong Zhou Geoffrey Ye Li FedML 31 16 0 03 May 2022
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
Communication Efficient Federated Learning via Ordered ADMM in a Fully Decentralized Setting Yicheng Chen Rick S. Blum Brian M. Sadler FedML 14 7 0 05 Feb 2022
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning Lokesh Nagalapatti Mahdi S. Hosseini FedML 27 75 0 23 Oct 2021
Communication Efficiency in Federated Learning: Achievements and Challenges Osama Shahid Seyedamin Pouriyeh R. Parizi Quan Z. Sheng Gautam Srivastava Liang Zhao FedML 40 74 0 23 Jul 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 412 0 14 Jul 2021
FedMix: Approximation of Mixup under Mean Augmented Federated Learning Tehrim Yoon Sumin Shin Sung Ju Hwang Eunho Yang FedML 27 165 0 01 Jul 2021
Joint Client Scheduling and Resource Allocation under Channel Uncertainty in Federated Learning Madhusanka Manimel Wadu S. Samarakoon M. Bennis 18 51 0 12 Jun 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 19 122 0 17 May 2021
Federated Few-Shot Learning with Adversarial Learning Chenyou Fan Jianwei Huang FedML 18 29 0 01 Apr 2021
Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks M. Salehi Ekram Hossain FedML 51 82 0 09 Dec 2020
Design and Analysis of Uplink and Downlink Communications for Federated Learning Sihui Zheng Cong Shen Xiang Chen 39 140 0 07 Dec 2020
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 27 49 0 25 Nov 2020
Fast-Convergent Federated Learning Hung T. Nguyen Vikash Sehwag Seyyedali Hosseinalipour Christopher G. Brinton M. Chiang H. Vincent Poor FedML 28 192 0 26 Jul 2020
Multi-Stage Hybrid Federated Learning over Large-Scale D2D-Enabled Fog Networks Seyyedali Hosseinalipour Sheikh Shams Azam Christopher G. Brinton Nicolò Michelusi Vaneet Aggarwal David J. Love H. Dai 29 91 0 18 Jul 2020
Federated Learning for Task and Resource Allocation in Wireless High Altitude Balloon Networks Sihua Wang Mingzhe Chen Changchuan Yin Walid Saad Choong Seon Hong Shuguang Cui H. Vincent Poor 36 67 0 19 Mar 2020
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence S. Raschka Joshua Patterson Corey J. Nolet AI4CE 24 484 0 12 Feb 2020
Crowdsourcing the Perception of Machine Teaching Jonggi Hong Kyungjun Lee June Xu Hernisa Kacorri HAI LRM 25 29 0 05 Feb 2020
FedDANE: A Federated Newton-Type Method Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 18 155 0 07 Jan 2020
Robust Aggregation for Federated Learning Krishna Pillutla Sham Kakade Zaïd Harchaoui FedML 37 629 0 31 Dec 2019
Communication-Efficient Local Decentralized SGD Methods Xiang Li Wenhao Yang Shusen Wang Zhihua Zhang 30 53 0 21 Oct 2019
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Felix Sattler K. Müller Wojciech Samek FedML 71 969 0 04 Oct 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 94 2,286 0 04 Jul 2019
Variational Federated Multi-Task Learning Luca Corinzia Ami Beuret J. M. Buhmann FedML 27 159 0 14 Jun 2019
Communication-Efficient Accurate Statistical Estimation Jianqing Fan Yongyi Guo Kaizheng Wang 19 110 0 12 Jun 2019
Fair Resource Allocation in Federated Learning Tian Li Maziar Sanjabi Ahmad Beirami Virginia Smith FedML 18 781 0 25 May 2019
Decentralized Bayesian Learning over Graphs Anusha Lalitha Xinghan Wang O. Kilinc Y. Lu T. Javidi F. Koushanfar FedML 28 25 0 24 May 2019
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms Jianyu Wang Gauri Joshi 33 348 0 22 Aug 2018
COLA: Decentralized Linear Learning Lie He An Bian Martin Jaggi 24 117 0 13 Aug 2018
A Distributed Second-Order Algorithm You Can Trust Celestine Mendler-Dünner Aurelien Lucchi Matilde Gargiani An Bian Thomas Hofmann Martin Jaggi 34 32 0 20 Jun 2018
Global linear convergence of Newton's method without strong-convexity or Lipschitz gradients Sai Praneeth Karimireddy Sebastian U. Stich Martin Jaggi 23 50 0 01 Jun 2018
Snap ML: A Hierarchical Framework for Machine Learning Celestine Mendler-Dünner Thomas Parnell Dimitrios Sarigiannis Nikolas Ioannou Andreea Anghel Gummadi Ravi Madhusudanan Kandasamy Haralambos Pozidis GP 17 26 0 16 Mar 2018
GIANT: Globally Improved Approximate Newton Method for Distributed Optimization Shusen Wang Farbod Roosta-Khorasani Peng Xu Michael W. Mahoney 36 127 0 11 Sep 2017
On the convergence properties of a $K$ -step averaging stochastic gradient descent algorithm for nonconvex optimization Fan Zhou Guojing Cong 46 232 0 03 Aug 2017
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 17 1,780 0 30 May 2017
Understanding and Optimizing the Performance of Distributed Machine Learning Applications on Apache Spark Celestine Mendler-Dünner Thomas Parnell Kubilay Atasu Manolis Sifalakis H. Pozidis 27 17 0 05 Dec 2016
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data Jialei Wang J. Lee M. Mahdavi Mladen Kolar Nathan Srebro 21 50 0 10 Oct 2016
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 139 1,201 0 16 Aug 2016
Efficient Distributed Learning with Sparsity Jialei Wang Mladen Kolar Nathan Srebro Tong Zhang FedML 26 151 0 25 May 2016