2024
DOI: 10.1109/access.2024.3403420
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Harnessing Learn Rate Schedule for Adaptive Deep Learning in LoRaWAN-IoT Localization

R. Swathika,
S. M. Dilip Kumar,
N. N. Srinidhi
et al.

Abstract: The learning rate is one of the most crucial hyper-parameters to regulate during the training of the Deep Learning (DL) models and optimizers. Adaptive learning rate algorithms try to automate the time-consuming process of manually setting a suitable learning rate, which is still exhausting. This research uses the learn rate schedule mechanism for training DL models. The learn rate schedule mechanism updates the learning rate for each step or iteration in DL models and optimizers for problem-solving. This pape… Show more

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