Federated Learning Approach for Lifetime Prediction of Semiconductor Lasers

Khouloud Abdelli; Helmut Griesser; Stephan Pachnicke

Federated Learning Approach for Lifetime Prediction of Semiconductor Lasers

Signal Processing 2022-03-24 v1 Machine Learning

Authors: Khouloud Abdelli , Helmut Griesser , Stephan Pachnicke

Abstract

A new privacy-preserving federated learning framework allowing laser manufacturers to collaboratively build a robust ML-based laser lifetime prediction model, is proposed. It achieves a mean absolute error of 0.1 years and a significant performance improvement

Keywords

federated learning laser lifetime prediction privacy-preserving semiconductor lasers machine learning

Cite

@article{arxiv.2203.12414,
  title  = {Federated Learning Approach for Lifetime Prediction of Semiconductor Lasers},
  author = {Khouloud Abdelli and Helmut Griesser and Stephan Pachnicke},
  journal= {arXiv preprint arXiv:2203.12414},
  year   = {2022}
}

Comments

Optical Fiber Communication Conference (OFC 2022)

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