Client-Adaptive Cross-Model Reconstruction Network for Modality-Incomplete Multimodal Federated Learning-Reference-Cited by-同舟云学术

Client-Adaptive Cross-Model Reconstruction Network for Modality-Incomplete Multimodal Federated Learning

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
language:
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Author:

Xiong Baochen¹^ORCID,Yang Xiaoshan²^ORCID,Song Yaguang²^ORCID,Wang Yaowei³^ORCID,Xu Changsheng²^ORCID

Affiliation:

1. Institute of Automation, Chinese Academy of Sciences, Peng Cheng Laboratory, & University of Chinese Academy of Sciences, Beijing, China

2. Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, & Peng Cheng Laboratory, Beijing, China

3. Peng Cheng Laboratory, Shenzhen, China

Funder

Beijing Natural Science Foundation

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3611757

Reference46 articles.

1. Durmus Alp Emre Acar , Yue Zhao , Ramon Matas Navarro , Matthew Mattina, Paul N Whatmough, and Venkatesh Saligrama. 2021 . Federated learning based on dynamic regularization. arXiv preprint arXiv:2111.04263. Durmus Alp Emre Acar, Yue Zhao, Ramon Matas Navarro, Matthew Mattina, Paul N Whatmough, and Venkatesh Saligrama. 2021. Federated learning based on dynamic regularization. arXiv preprint arXiv:2111.04263.

2. Gustavo Aguilar Viktor Rozgić and Weiran Wang. 2019. Multimodal and multi-view models for emotion recognition. arXiv preprint arXiv:1906.10198. Gustavo Aguilar Viktor Rozgić and Weiran Wang. 2019. Multimodal and multi-view models for emotion recognition. arXiv preprint arXiv:1906.10198.

3. Manoj Ghuhan Arivazhagan , Vinay Aggarwal , Aaditya Kumar Singh, and Sunav Choudhary . 2019 . Federated learning with personalization layers. arXiv preprint arXiv:1912.00818. Manoj Ghuhan Arivazhagan, Vinay Aggarwal, Aaditya Kumar Singh, and Sunav Choudhary. 2019. Federated learning with personalization layers. arXiv preprint arXiv:1912.00818.

4. Smart Assistive Architecture for the Integration of IoT Devices, Robotic Systems, and Multimodal Interfaces in Healthcare Environments

5. Deep Adversarial Learning for Multi-Modality Missing Data Completion

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