Abstract: This paper investigates the impact of client and server learning rates on training deep neural networks in Federated Learning (FL). While previous research has primarily focused on ...
This study presents a bio-inspired control framework for soft robots, enhancing tracking accuracy by over 44% under ...
Abstract: Learning rate is a crucial parameter in training of neural networks. A properly tuned learning rate leads to faster training and higher test accuracy. In this paper, we propose a Lipschitz ...
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