A Survey on Distributed Machine Learning

20 December 2019

Papers citing "A Survey on Distributed Machine Learning"

50 / 186 papers shown

Title
Toward Safety-First Human-Like Decision Making for Autonomous Vehicles in Time-Varying Traffic Flow Xiao Wang Junru Yu Jun Huang Qiong Wu Ljubo Vacic Changyin Sun 19 0 0 17 Jun 2025
UniVarFL: Uniformity and Variance Regularized Federated Learning for Heterogeneous Data Sunny Gupta Nikita Jangid Amit Sethi FedML 10 0 0 09 Jun 2025
Regularized Federated Learning for Privacy-Preserving Dysarthric and Elderly Speech Recognition Tao Zhong Mengzhe Geng Shujie Hu Guinan Li Xunying Liu 17 0 0 02 Jun 2025
Enhancing Parallelism in Decentralized Stochastic Convex Optimization Ofri Eisen Ron Dorfman Kfir Y. Levy 35 0 0 01 Jun 2025
Coded Robust Aggregation for Distributed Learning under Byzantine Attacks Chengxi Li Ming Xiao Mikael Skoglund AAML OOD 12 0 0 17 May 2025
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 104 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 45 0 0 06 May 2025
Lazy But Effective: Collaborative Personalized Federated Learning with Heterogeneous Data Ljubomir Rokvic Panayiotis Danassis Boi Faltings FedML 163 0 0 05 May 2025
Scalability and Maintainability Challenges and Solutions in Machine Learning: Systematic Literature Review Karthik Shivashankar Ghadi S. Al Hajj Antonio Martini 110 0 0 15 Apr 2025
Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling Chaojian Li Zhifan Ye Massimiliano Lupo Pasini Jong Youl Choi Cheng Wan Y. Lin Prasanna Balaprakash 86 1 0 10 Apr 2025
PDSL: Privacy-Preserved Decentralized Stochastic Learning with Heterogeneous Data Distribution Lina Wang Yunsheng Yuan Chunxiao Wang Feng Li FedML 117 0 0 31 Mar 2025
Federated Learning with Differential Privacy: An Utility-Enhanced Approach Kanishka Ranaweera Dinh C. Nguyen P. Pathirana David B. Smith Ming Ding Thierry Rakotoarivelo A. Seneviratne FedML 86 0 0 27 Mar 2025
RESFL: An Uncertainty-Aware Framework for Responsible Federated Learning by Balancing Privacy, Fairness and Utility in Autonomous Vehicles Dawood Wasif T. Moore Jin-Hee Cho 73 0 0 20 Mar 2025
Distributed Multi-Head Learning Systems for Power Consumption Prediction Jia-Hao Syu Jerry Chun-Wei Lin Philip S. Yu 90 1 0 21 Jan 2025
Resilient Peer-to-peer Learning based on Adaptive Aggregation Chandreyee Bhowmick Xenofon Koutsoukos 65 0 0 08 Jan 2025
Accelerated Methods with Compressed Communications for Distributed Optimization Problems under Data Similarity Dmitry Bylinkin Aleksandr Beznosikov 146 1 0 21 Dec 2024
Learn More by Using Less: Distributed Learning with Energy-Constrained Devices Roberto Pereira Cristian J. Vaca-Rubio Luis Blanco FedML 81 0 0 03 Dec 2024
SoK: Decentralized AI (DeAI) Zhipeng Wang Rui Sun Elizabeth Lui Vatsal Shah Xihan Xiong Jiahao Sun Davide Crapis William Knottenbelt 196 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 88 6 0 08 Nov 2024
ROSS:RObust decentralized Stochastic learning based on Shapley values Lina Wang Yunsheng Yuan Feng Li Lingjie Duan FedML 85 0 0 01 Nov 2024
Meta-Learning for Speeding Up Large Model Inference in Decentralized Environments Yuzhe Yang Yipeng Du Ahmad Farhan Claudio Angione Yue Zhao Harry Yang Fielding Johnston James Buban Patrick Colangelo 103 0 0 28 Oct 2024
Distributed Networked Multi-task Learning Lingzhou Hong Alfredo García 28 1 0 04 Oct 2024
Temporal Predictive Coding for Gradient Compression in Distributed Learning Adrian Edin Zheng Chen Michel Kieffer Mikael Johansson 51 1 0 03 Oct 2024
Accelerated Stochastic ExtraGradient: Mixing Hessian and Gradient Similarity to Reduce Communication in Distributed and Federated Learning Dmitry Bylinkin Kirill Degtyarev Aleksandr Beznosikov FedML 68 0 0 22 Sep 2024
An Efficient Privacy-aware Split Learning Framework for Satellite Communications Jianfei Sun Cong Wu Shahid Mumtaz Junyi Tao Mingsheng Cao Mei Wang Valerio Frascolla 73 5 0 13 Sep 2024
Slicing Input Features to Accelerate Deep Learning: A Case Study with Graph Neural Networks Zhengjia Xu Dingyang Lyu Jinghui Zhang GNN 108 0 0 21 Aug 2024
Towards a Standardized Representation for Deep Learning Collective Algorithms Jinsun Yoo William Won Meghan Cowan Nan Jiang Benjamin Klenk Srinivas Sridharan Tushar Krishna 90 1 0 20 Aug 2024
Federated Clustering: An Unsupervised Cluster-Wise Training for Decentralized Data Distributions Mirko Nardi Lorenzo Valerio A. Passarella FedML 95 0 0 20 Aug 2024
Ordered Momentum for Asynchronous SGD Chang-Wei Shi Yi-Rui Yang Wu-Jun Li ODL 167 0 0 27 Jul 2024
Intelligent Cross-Organizational Process Mining: A Survey and New Perspectives Yiyuan Yang Zheshun Wu Yong Chu Zhenghua Chen Zenglin Xu Qingsong Wen 56 0 0 15 Jul 2024
Impact of Network Topology on Byzantine Resilience in Decentralized Federated Learning Siddhartha Bhattacharya Daniel Helo Joshua Siegel 88 1 0 06 Jul 2024
On the Performance and Memory Footprint of Distributed Training: An Empirical Study on Transformers Zhengxian Lu Fangyu Wang Zhiwei Xu Fei Yang Tao Li 70 1 0 02 Jul 2024
Large Batch Analysis for Adagrad Under Anisotropic Smoothness Yuxing Liu Boyao Wang Tong Zhang 57 6 0 21 Jun 2024
Training Through Failure: Effects of Data Consistency in Parallel Machine Learning Training Ray Cao Sherry Luo Steve Gan Sujeeth Jinesh 56 0 0 08 Jun 2024
Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients Weijun Li Xingliang Yuan Mark Dras PILM 67 2 0 03 Jun 2024
Local Methods with Adaptivity via Scaling Saveliy Chezhegov Sergey Skorik Nikolas Khachaturov Danil Shalagin A. Avetisyan Aleksandr Beznosikov Martin Takáč Yaroslav Kholodov Alexander Gasnikov 110 3 0 02 Jun 2024
Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data Xiaolu Wang Yuchang Sun Hoi-To Wai Jun Zhang 75 0 0 27 May 2024
A GPU-Accelerated Bi-linear ADMM Algorithm for Distributed Sparse Machine Learning A. Olama Andreas Lundell Jan Kronqvist Elham Ahmadi Eduardo Camponogara 61 0 0 25 May 2024
Towards Energy-Aware Federated Learning via MARL: A Dual-Selection Approach for Model and Client Jun Xia Yi Zhang Yiyu Shi 65 1 0 13 May 2024
FedStale: leveraging stale client updates in federated learning Angelo Rodio Giovanni Neglia FedML 70 5 0 07 May 2024
Mean Aggregator Is More Robust Than Robust Aggregators Under Label Poisoning Attacks Jie Peng Weiyu Li Qing Ling OOD 81 1 0 21 Apr 2024
AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes Youshao Xiao Lin Ju Zhenglei Zhou Siyuan Li Zhaoxin Huan ... Rujie Jiang Lin Wang Xiaolu Zhang Lei Liang Jun Zhou 59 1 0 15 Apr 2024
Optimizing Malware Detection in IoT Networks: Leveraging Resource-Aware Distributed Computing for Enhanced Security Sreenitha Kasarapu Sanket Shukla Sai Manoj P D 29 0 0 12 Apr 2024
Enhancing IoT Malware Detection through Adaptive Model Parallelism and Resource Optimization Sreenitha Kasarapu Sanket Shukla Sai Manoj P D 42 1 0 12 Apr 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 103 8 0 09 Apr 2024
HSViT: Horizontally Scalable Vision Transformer Chenhao Xu Chang-Tsun Li Chee Peng Lim Douglas Creighton ViT 65 2 0 08 Apr 2024
MODNO: Multi Operator Learning With Distributed Neural Operators Zecheng Zhang 130 8 0 03 Apr 2024
Machine Unlearning for Traditional Models and Large Language Models: A Short Survey Yi Xu AILaw MU 76 8 0 01 Apr 2024
MAPL: Model Agnostic Peer-to-peer Learning Sayak Mukherjee Andrea Simonetto Hadi Jamali Rad 130 0 0 28 Mar 2024
FSD-Inference: Fully Serverless Distributed Inference with Scalable Cloud Communication Joe Oakley Hakan Ferhatosmanoglu 62 2 0 22 Mar 2024