Upgrade of Deep Neural Network-based Optical Monitors by Communication-Efficient Federated Learning
Author:
Affiliation:
1. Hitachi Ltd.,Research and Development Group,Kokubunji, Tokyo,Japan,185-8601
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10115459/10115461/10117269.pdf?arnumber=10117269
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1. One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers;morcos;NeurIPS 2019,0
2. Compressing Model before Federated Learning by Transferrable Surrogate Lottery Ticket
3. Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data
4. Optical Status Representation by Collaborative and Unsupervised Learning
5. Vertical federated learning for privacy-preserving ML model development in partially disaggregated networks;hashemi;ECOC,2021
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