88 citations · 94 across the 4 of their papers we have counts for
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cs.LG2023
Reduced Precision Floating-Point Optimization for Deep Neural Network On-Device Learning on MicroControllers
Davide Nadalini, Manuele Rusci, Luca Benini +1
Enabling On-Device Learning (ODL) for Ultra-Low-Power Micro-Controller Units (MCUs) is a key step for post-deployment adaptation and fine-tuning of Deep Neural Network (DNN) models…
cs.LG2021★ 88 cited
A TinyML Platform for On-Device Continual Learning with Quantized Latent Replays
Leonardo Ravaglia, Manuele Rusci, Davide Nadalini +3
In the last few years, research and development on Deep Learning models and techniques for ultra-low-power devices in a word, TinyML has mainly focused on a train-then-deploy assum…