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Pipeline Parallelism in Distributed Deep Learning for Diabetic Retinopathy Classification

Procedia computer science, 2022, Vol.215, p.393-402

2022

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A Systematic Review of Distributed Deep Learning Frameworks for Big Data

Intelligent Computing Methodologies, p.242-256

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OASR-WFBP: An overlapping aware start-up sharing gradient merging strategy for efficient communication in distributed deep learning

Journal of parallel and distributed computing, 2025-02, Vol.196, p.104997, Article 104997

2025

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NetShield: An in-network architecture against byzantine failures in distributed deep learning

Computer networks (Amsterdam, Netherlands : 1999), 2023-12, Vol.237, p.110081, Article 110081

2023

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Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data

Future generation computer systems, 2022-03, Vol.128, p.406-419

2022

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Deep Learning for Distributed Optimization: Applications to Wireless Resource Management

IEEE journal on selected areas in communications, 2019-10, Vol.37 (10), p.2251-2266

2019

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D3: Differential Testing of Distributed Deep Learning with Model Generation

IEEE transactions on software engineering, 2024-09, p.1-16

2024

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Distributed Analytics For Big Data: A Survey

Neurocomputing (Amsterdam), 2024-03, Vol.574, p.127258, Article 127258

2024

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Toward Edge-Based Deep Learning in Industrial Internet of Things

IEEE internet of things journal, 2020-05, Vol.7 (5), p.4329-4341

2020

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Blockchain-escorted distributed deep learning with collaborative model aggregation towards 6G networks

Future generation computer systems, 2023-04, Vol.141, p.555-566

2023

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Privacy-Preserving distributed deep learning based on secret sharing

Information sciences, 2020-07, Vol.527, p.108-127

2020

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Deep-Distributed-Learning-Based POI Recommendation Under Mobile-Edge Networks

IEEE internet of things journal, 2023-01, Vol.10 (1), p.303-317

2023

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Collaborate Edge and Cloud Computing With Distributed Deep Learning for Smart City Internet of Things

IEEE internet of things journal, 2020-09, Vol.7 (9), p.8099-8110

2020

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Decentralized Distributed Multi-institutional PET Image Segmentation Using a Federated Deep Learning Framework

Clinical nuclear medicine, 2022-07, Vol.47 (7), p.606-617

2022

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Communication optimization strategies for distributed deep neural network training: A survey

Journal of parallel and distributed computing, 2021-03, Vol.149, p.52-65

2021

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A novel device placement approach based on position-aware subgraph neural networks

Neurocomputing (Amsterdam), 2024-05, Vol.582, p.127501, Article 127501

2024

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PipePar: Enabling fast DNN pipeline parallel training in heterogeneous GPU clusters

Neurocomputing (Amsterdam), 2023-10, Vol.555, p.126661, Article 126661

2023

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Scalable and Practical Natural Gradient for Large-Scale Deep Learning

IEEE transactions on pattern analysis and machine intelligence, 2022-01, Vol.44 (1), p.404-415

2022

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Communication Optimization Algorithms for Distributed Deep Learning Systems: A Survey

IEEE transactions on parallel and distributed systems, 2023-12, Vol.34 (12), p.3294-3308

2023

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Self-aware distributed deep learning framework for heterogeneous IoT edge devices

Future generation computer systems, 2021-12, Vol.125, p.908-920

2021

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Computation offloading and resource allocation based on distributed deep learning and software defined mobile edge computing

Computer networks (Amsterdam, Netherlands : 1999), 2022-03, Vol.205, p.108732, Article 108732

2022

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Cloud-edge-device collaboration mechanisms of deep learning models for smart robots in mass personalization

Robotics and computer-integrated manufacturing, 2022-10, Vol.77, p.102351, Article 102351

2022

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Comparative Study on Distributed Lightweight Deep Learning Models for Road Pothole Detection

Sensors (Basel, Switzerland), 2023-04, Vol.23 (9), p.4347

2023

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FedDCS: A distributed client selection framework for cross device federated learning

Future generation computer systems, 2023-07, Vol.144, p.24-36

2023

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GreenFlow: A Carbon-Efficient Scheduler for Deep Learning Workloads

IEEE transactions on parallel and distributed systems, 2024-10, p.1-17

2024

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Pipeline Parallelism in Distributed Deep Learning for Diabetic Retinopathy Classification

A Systematic Review of Distributed Deep Learning Frameworks for Big Data

OASR-WFBP: An overlapping aware start-up sharing gradient merging strategy for efficient communication in distributed deep learning

NetShield: An in-network architecture against byzantine failures in distributed deep learning

Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data

Deep Learning for Distributed Optimization: Applications to Wireless Resource Management

D3: Differential Testing of Distributed Deep Learning with Model Generation

Distributed Analytics For Big Data: A Survey

Toward Edge-Based Deep Learning in Industrial Internet of Things

Blockchain-escorted distributed deep learning with collaborative model aggregation towards 6G networks

Privacy-Preserving distributed deep learning based on secret sharing

Deep-Distributed-Learning-Based POI Recommendation Under Mobile-Edge Networks

Collaborate Edge and Cloud Computing With Distributed Deep Learning for Smart City Internet of Things

Decentralized Distributed Multi-institutional PET Image Segmentation Using a Federated Deep Learning Framework

Communication optimization strategies for distributed deep neural network training: A survey

A novel device placement approach based on position-aware subgraph neural networks

PipePar: Enabling fast DNN pipeline parallel training in heterogeneous GPU clusters

Scalable and Practical Natural Gradient for Large-Scale Deep Learning

Communication Optimization Algorithms for Distributed Deep Learning Systems: A Survey

Self-aware distributed deep learning framework for heterogeneous IoT edge devices

Computation offloading and resource allocation based on distributed deep learning and software defined mobile edge computing

Cloud-edge-device collaboration mechanisms of deep learning models for smart robots in mass personalization

Comparative Study on Distributed Lightweight Deep Learning Models for Road Pothole Detection

FedDCS: A distributed client selection framework for cross device federated learning

GreenFlow: A Carbon-Efficient Scheduler for Deep Learning Workloads

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