A Survey of Model Compression and Its Feedback Mechanism in Federated Learning-Reference-Cited by-同舟云学术

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A Survey of Model Compression and Its Feedback Mechanism in Federated Learning

Published:2024-06-10 Issue: Volume:93 Page:37-42
ISSN:
Container-title:The Fifth Workshop on Intelligent Cross-Data Analysis and Retrieval
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Author:

Le Duy-Dong¹^ORCID,Tran Anh-Khoa²^ORCID,Pham The-Bao³^ORCID,Huynh Tuong-Nguyen¹^ORCID

Affiliation:

1. Industrial University of Ho Chi Minh City, Vietnam

2. National Institute of Information and Communications Technology, Japan

3. Saigon University, Vietnam

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3643488.3660293

Reference55 articles.

1. An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

2. Nima Aghli and Eraldo Ribeiro. 2021. Combining Weight Pruning and Knowledge Distillation For CNN Compression. 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2021), 3185–3192.

3. Alyazeed Albasyoni, Mher Safaryan, Laurent Condat, and Peter Richtárik. 2020. Optimal gradient compression for distributed and federated learning. arXiv preprint arXiv:2010.03246 (2020).

4. Deep Model Compression and Architecture Optimization for Embedded Systems: A Survey;Berthelier Anthony;Journal of Signal Processing Systems,2020

5. Yaohui Cai, Zhewei Yao, Zhen Dong, Amir Gholami, Michael W Mahoney, and Kurt Keutzer. 2020. ZeroQ: A Novel Zero Shot Quantization Framework. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 13169–13178.

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