A research on intelligent recommendation algorithms based on federated learning

Yue Wu

doi:10.1117/12.3004909

9 October 2023 A research on intelligent recommendation algorithms based on federated learning

Yue Wu

Proceedings Volume 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023); 127910T (2023) https://doi.org/10.1117/12.3004909
Event: Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 2023, Qingdao, SD, China

Abstract

Federated learning is a promising new paradigm for privacy protection. By dispersing training data storage locally rather than centrally constructing large-scale datasets, federated learning provides a mechanism for training models that protects privacy for various data-hungry applications, such as recommendation algorithms for mitigating information overload. This article implements a family of algorithms with common characteristics in a federated learning framework for model parameter transfer. Through comparative experiments, the performance differences of these algorithms under this federated learning framework are examined, and their model performance is compared and analyzed under their respective centralized learning forms. The conclusion is that the algorithm family combined with neural networks has higher performance and is more stable in this federated learning framework, with less performance loss.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yue Wu "A research on intelligent recommendation algorithms based on federated learning", Proc. SPIE 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 127910T (9 October 2023); https://doi.org/10.1117/12.3004909

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