- Blockchain Assisted Decentralized Federated Learning 🔍
- Xiumei Deng🔍
- Client selection for federated learning using combinatorial multi ...🔍
- Delayed Gradient Averaging🔍
- A bidirectional DNN partition mechanism for efficient pipeline ...🔍
- Trustworthy DNN Partition for Blockchain|enabled ...🔍
- Curated collection of papers in machine learning systems🔍
- Distributed DNN Inference With Fine|Grained Model Partitioning in ...🔍
Low|Latency Federated Learning With DNN Partition in Distributed ...
Kang Wei (韦康) - Google Scholar
2023. Low-latency Federated Learning with DNN Partition in Distributed Industrial IoT Networks. X Deng, J Li, C Ma, K Wei, L Shi, M Ding, W Chen. IEEE Journal ...
Blockchain Assisted Decentralized Federated Learning (BLADE-FL ...
Low-Latency Federated Learning With DNN Partition in Distributed Industrial IoT Networks. Xiumei Deng, Jun Li, Chuan Ma, Kang Wei, Long Shi, Ming Ding, Wen ...
CoopFL: Accelerating federated learning with DNN partitioning and ...
36, (8) 2022, pp. 8485–8493. https://doi.org/10.1609/aaai.v36i8.20825; Gupta, Distributed learning of deep neural network over multiple ...
Xiumei Deng | Papers With Code
Trustworthy DNN Partition for Blockchain-enabled Digital Twin in Wireless ... As an efficient distributed machine learning approach, Federated learning ...
Client selection for federated learning using combinatorial multi ...
Low-Latency Federated Learning With DNN Partition in Distributed Industrial IoT Networks. IEEE Journal on Selected Areas in Communications, 2022. An ...
Kang Wei (韦康) - Google 学术搜索
Low-latency Federated Learning with DNN Partition in Distributed Industrial IoT Networks. X Deng, J Li, C Ma, K Wei, L Shi, M Ding, W Chen. IEEE Journal on ...
Xiumei Deng, Jun Li, Chuan Ma, Kang Wei, Long Shi, Ming Ding and Wen Chen,“Low-latency. Federated Learning with DNN Partition in Distributed Industrial IoT ...
Delayed Gradient Averaging: Tolerate the Communication Latency ...
Abstract. Federated Learning is an emerging direction in distributed machine learning that enables jointly training a model without sharing the data.
A bidirectional DNN partition mechanism for efficient pipeline ...
proposed for large-scale DNN training by fully utilizing the computation and storage power of the distributed cluster. Cloud data centers ...
Trustworthy DNN Partition for Blockchain-enabled ... - SciEngine
Zomaya, “Federated learning with nesterov accelerated gradient,” IEEE. Trans. Parallel Distributed Syst., vol. 33, no. 12, pp. 4863–4873, 2022. 2 C. Zhou, J ...
Curated collection of papers in machine learning systems - GitHub
... Reduce for Distributed DNN Training in Optical Interconnect Systems ... [arxiv'24] Decoupled Vertical Federated Learning for Practical Training on Vertically ...
Distributed DNN Inference With Fine-Grained Model Partitioning in ...
... study the issue of distributed DNN inference under specific delay constraints. ... federated learning based algorithm for personalized DNN inference in MEC ...
Communication-Efficient Federated Learning with Adaptive ...
Our extensive array of experimental results show that APF can reduce data ... Scalable distributed dnn training using commodity gpu cloud computing. In ...
Low-Latency Federated Learning With DNN Partition in Distributed Industrial IoT Networks · pdf icon · hmtl icon · Xiumei Deng, Jun Li, Chuan Ma, Kang Wei, Long ...
Model-Distributed DNN Training for Memory-Constrained Edge ...
Federated learning mechanisms train DNN models distributively across workers ... lower storage and memory requirements as compared to data- distributed learning.
Efficient Edge Collaborative Pipeline Training - Shengyuan Ye
Partition DNN into stages. Split mini-batch into micro ... training, which jointly considers both the response latency and data distribution divergence.
Design of a Quantization-Based DNN Delta Compression ...
... Federated Learning. Haoyu Jin, Sian Jin + Show ... Low-Latency Federated Learning With DNN Partition in Distributed Industrial IoT Networks.
Efficient federated learning for distributed neuroimaging data
... data distributions across federated clients through the adoption of two distinct data partitioning ... “$GAZELLE$: a low latency framework for secure neural ...
Distributed machine learning on Edge computing systems
This DNN partitioning-based federated learning (DPFL) system is further ... training latency, and communication cost. DOI. https://doi.org/10.17630/sta ...
Open-Source Federated Learning Frameworks for IoT - MDPI
Federated Learning Challenges. 3.1. Data Partitioning. There are two different cases of how data are distributed in the IoT system [23]:.