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Found 2 papers, 2 papers with code
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers
To address this challenge, neural architecture search (NAS) promises to help design accurate ML models that meet the tight MCU memory, latency and energy constraints.
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Federated Learning Based on Dynamic Regularization
We propose a novel federated learning method for distributively training neural network models, where the server orchestrates cooperation between a subset of randomly chosen devices in each round.
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