A Survey on Distributed Machine Learning

20 December 2019

Papers citing "A Survey on Distributed Machine Learning"

50 / 64 papers shown

Title
Trial and Trust: Addressing Byzantine Attacks with Comprehensive Defense Strategy Gleb Molodtsov Daniil Medyakov Sergey Skorik Nikolas Khachaturov Shahane Tigranyan Vladimir Aletov A. Avetisyan Martin Takáč Aleksandr Beznosikov AAML 35 0 0 12 May 2025
Decentralized Distributed Proximal Policy Optimization (DD-PPO) for High Performance Computing Scheduling on Multi-User Systems Matthew Sgambati Aleksandar Vakanski Matthew Anderson 32 0 0 06 May 2025
Lazy But Effective: Collaborative Personalized Federated Learning with Heterogeneous Data Ljubomir Rokvic Panayiotis Danassis Boi Faltings FedML 43 0 0 05 May 2025
PDSL: Privacy-Preserved Decentralized Stochastic Learning with Heterogeneous Data Distribution Lina Wang Yunsheng Yuan Chunxiao Wang Feng Li FedML 43 0 0 31 Mar 2025
Distributed Multi-Head Learning Systems for Power Consumption Prediction Jia-Hao Syu Jerry Chun-Wei Lin Philip S. Yu 31 1 0 21 Jan 2025
SoK: Decentralized AI (DeAI) Zhipeng Wang Rui Sun Elizabeth Lui Vatsal Shah Xihan Xiong Jiahao Sun Davide Crapis William Knottenbelt 101 1 0 26 Nov 2024
Acceleration for Deep Reinforcement Learning using Parallel and Distributed Computing: A Survey Zhihong Liu Xin Xu Peng Qiao Dongsheng Li OffRL 22 2 0 08 Nov 2024
Ordered Momentum for Asynchronous SGD Chang-Wei Shi Yi-Rui Yang Wu-Jun Li ODL 59 0 0 27 Jul 2024
Towards Energy-Aware Federated Learning via MARL: A Dual-Selection Approach for Model and Client Jun Xia Yi Zhang Yiyu Shi 31 0 0 13 May 2024
Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey Feng Liang Zhen Zhang Haifeng Lu Victor C. M. Leung Yanyi Guo Xiping Hu GNN 37 6 0 09 Apr 2024
Impact of network topology on the performance of Decentralized Federated Learning Luigi Palmieri C. Boldrini Lorenzo Valerio A. Passarella M. Conti 39 6 0 28 Feb 2024
Perfect Multi-User Distributed Computing Ali Khalesi P. Elia 16 2 0 04 Feb 2024
Machine learning and domain decomposition methods -- a survey A. Klawonn M. Lanser J. Weber AI4CE 24 7 0 21 Dec 2023
SCoTTi: Save Computation at Training Time with an adaptive framework Ziyu Li Enzo Tartaglione Van-Tam Nguyen 33 0 0 19 Dec 2023
Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights Maryam Ben Driss Essaid Sabir H. Elbiaze Walid Saad 30 7 0 07 Dec 2023
SPIRT: A Fault-Tolerant and Reliable Peer-to-Peer Serverless ML Training Architecture Amine Barrak Mayssa Jaziri Ranim Trabelsi Fehmi Jaafar Fábio Petrillo 44 2 0 25 Sep 2023
Robust Fully-Asynchronous Methods for Distributed Training over General Architecture Zehan Zhu Ye Tian Yan Huang Jinming Xu Shibo He OOD 25 2 0 21 Jul 2023
Variance-reduced accelerated methods for decentralized stochastic double-regularized nonconvex strongly-concave minimax problems Gabriel Mancino-Ball Yangyang Xu 20 8 0 14 Jul 2023
A Survey From Distributed Machine Learning to Distributed Deep Learning Mohammad Dehghani Zahra Yazdanparast 23 0 0 11 Jul 2023
Incentive Allocation in Vertical Federated Learning Based on Bankruptcy Problem Afsana Khan M. T. Thij F. Thuijsman A. Wilbik FedML 28 2 0 07 Jul 2023
Artificial Collective Intelligence Engineering: a Survey of Concepts and Perspectives Roberto Casadei AI4CE 18 15 0 11 Apr 2023
Cloudless-Training: A Framework to Improve Efficiency of Geo-Distributed ML Training W. Tan Xiao Shi Cunchi Lv Xiaofang Zhao FedML 31 1 0 09 Mar 2023
Architecting Peer-to-Peer Serverless Distributed Machine Learning Training for Improved Fault Tolerance Amine Barrak Fábio Petrillo Fehmi Jaafar 29 2 0 27 Feb 2023
Federated Gradient Matching Pursuit Halyun Jeong Deanna Needell Jing Qin FedML 37 1 0 20 Feb 2023
On Feasibility of Server-side Backdoor Attacks on Split Learning Behrad Tajalli Oguzhan Ersoy S. Picek FedML SILM 45 8 0 19 Feb 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities Aleksandr Beznosikov Martin Takáč Alexander Gasnikov 29 10 0 15 Feb 2023
A Robust Classification Framework for Byzantine-Resilient Stochastic Gradient Descent Shashank Reddy Chirra K. Nadimpalli Shrisha Rao 27 0 0 16 Jan 2023
TAPS: Topology-Aware Intra-Operator Parallelism Strategy Searching Algorithm for Deep Neural Networks Peng Liang Hao Zheng Teng Su Linbo Qiao Dongsheng Li 27 0 0 11 Jan 2023
AI2: The next leap toward native language based and explainable machine learning framework J. Dessureault Daniel Massicotte 14 1 0 09 Jan 2023
FedSkip: Combatting Statistical Heterogeneity with Federated Skip Aggregation Ziqing Fan Yanfeng Wang Jiangchao Yao Lingjuan Lyu Ya Zhang Qinghua Tian FedML 21 20 0 14 Dec 2022
Fair and Efficient Distributed Edge Learning with Hybrid Multipath TCP Shiva Raj Pokhrel Jinho Choi A. Walid 30 6 0 03 Nov 2022
Client Selection in Federated Learning: Principles, Challenges, and Opportunities Lei Fu Huan Zhang Ge Gao Mi Zhang Xin Liu FedML 37 118 0 03 Nov 2022
Distributed Graph Neural Network Training: A Survey Yingxia Shao Hongzheng Li Xizhi Gu Hongbo Yin Yawen Li Xupeng Miao Wentao Zhang Bin Cui Lei Chen GNN AI4CE 11 56 0 01 Nov 2022
Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings Ryan Yang Haizhou Du Andre Wibisono Patrick Baker 11 1 0 28 Oct 2022
tf.data service: A Case for Disaggregating ML Input Data Processing Andrew Audibert Yangrui Chen D. Graur Ana Klimovic Jiří Šimša C. A. Thekkath 44 16 0 26 Oct 2022
Local Graph-homomorphic Processing for Privatized Distributed Systems Elsa Rizk Stefan Vlaski Ali H. Sayed FedML 34 1 0 26 Oct 2022
TRBoost: A Generic Gradient Boosting Machine based on Trust-region Method Jiaqi Luo Zihao Wei Junkai Man Shi-qian Xu 26 8 0 28 Sep 2022
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization Xingyou Song Sagi Perel Chansoo Lee Greg Kochanski Daniel Golovin 31 26 0 27 Jul 2022
Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing Wei Xu Zhaohui Yang Derrick Wing Kwan Ng Marco Levorato Yonina C. Eldar Mérouane Debbah 28 398 0 01 Jun 2022
Byzantine-Robust Online and Offline Distributed Reinforcement Learning Yiding Chen Xuezhou Zhang Kaipeng Zhang Mengdi Wang Xiaojin Zhu OffRL 26 16 0 01 Jun 2022
Privacy-Preserving Distributed Machine Learning Made Faster Z. L. Jiang Jiajing Gu Hongxiao Wang Yulin Wu Jun-bin Fang Siu-Ming Yiu Wenjian Luo Xuan Wang FedML 11 3 0 12 May 2022
Byzantine Fault Tolerance in Distributed Machine Learning : a Survey Djamila Bouhata Hamouma Moumen Moumen Hamouma Ahcène Bounceur AI4CE 27 7 0 05 May 2022
A Comprehensive Review on Blockchains for Internet of Vehicles: Challenges and Directions Brian Hildebrand Mohamed Baza Tara Salman Fathi H. Amsaad Abdul Razaqu Abdullah Alourani 33 45 0 21 Mar 2022
FlexBlock: A Flexible DNN Training Accelerator with Multi-Mode Block Floating Point Support Seock-Hwan Noh Jahyun Koo Seunghyun Lee Jongse Park Jaeha Kung AI4CE 32 17 0 13 Mar 2022
Similarity-based Label Inference Attack against Training and Inference of Split Learning Junlin Liu Xinchen Lyu Qimei Cui Xiaofeng Tao FedML 32 26 0 10 Mar 2022
FLoBC: A Decentralized Blockchain-Based Federated Learning Framework M. C. Ghanem Fadi Dawoud Habiba Gamal E. Soliman Hossam Sharara Tamer El-Batt 21 10 0 22 Dec 2021
Compare Where It Matters: Using Layer-Wise Regularization To Improve Federated Learning on Heterogeneous Data Ha Min Son M. Kim T. Chung FedML 19 9 0 01 Dec 2021
HeterPS: Distributed Deep Learning With Reinforcement Learning Based Scheduling in Heterogeneous Environments Ji Liu Zhihua Wu Dianhai Yu Yanjun Ma Danlei Feng Minxu Zhang Xinxuan Wu Xuefeng Yao Dejing Dou 18 44 0 20 Nov 2021
Fairness, Integrity, and Privacy in a Scalable Blockchain-based Federated Learning System Timon Rückel Johannes Sedlmeir Peter Hofmann FedML 19 58 0 11 Nov 2021
FedHe: Heterogeneous Models and Communication-Efficient Federated Learning Chan Yun Hin Edith C.H. Ngai FedML 19 24 0 19 Oct 2021