Search Results for author: Davide Nadalini

Found 2 papers, 1 papers with code

Reduced Precision Floating-Point Optimization for Deep Neural Network On-Device Learning on MicroControllers

1 code implementation30 May 2023 Davide Nadalini, Manuele Rusci, Luca Benini, Francesco Conti

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 in future TinyML applications.

Continual Learning Image Classification +1

A TinyML Platform for On-Device Continual Learning with Quantized Latent Replays

no code implementations20 Oct 2021 Leonardo Ravaglia, Manuele Rusci, Davide Nadalini, Alessandro Capotondi, Francesco Conti, Luca Benini

In this work, we introduce a HW/SW platform for end-to-end CL based on a 10-core FP32-enabled parallel ultra-low-power (PULP) processor.

Continual Learning Quantization

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