Personalized Federated Continual Learning for Task-Incremental Biometrics-Reference-Cited by-同舟云学术

Personalized Federated Continual Learning for Task-Incremental Biometrics

Author:

Li Dongdong¹^ORCID,Huang Nan¹,Wang Zhe¹^ORCID,Yang Hai¹^ORCID

Affiliation:

1. Computer Science and Technology, East China University of Science and Technology, Shanghai, China

Funder

Natural Science Foundation of China

Shanghai Science and Technology Program “Federated Based Cross-Domain and Cross-Task Incremental Learning”

Shanghai Science and Technology Program “Distributed and Generative Few-Shot Algorithm and Theory Research”

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

Reference43 articles.

1. Three scenarios for continual learning;van de ven;arXiv 1904 07734,2019

2. La-MAML: Look-ahead meta learning for continual learning;gupta;arXiv 2007 13904,2020

4. Learning to learn without forgetting by maximizing transfer and minimizing interference;riemer;arXiv 1810 11910,2019

5. Meta continual learning;vuorio;arXiv 1806 06928,2018

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