Recent advances in Tiny Machine Learning (TinyML) empower low-footprint embedded
devices for real-time on-device Machine Learning (ML). While many acknowledge the …

In the context of TinyML, many research efforts have been devoted to designing forward
topologies to support On-Device Learning. Reaching this target would bring numerous …

This letter addresses the challenging problem of performing on-device online learning for a
neural network to accomplish a regression task, under extreme memory and processing …

An interesting research challenge for the TinyML community concerns the capability to
achieve accurate online incremental learning for a regression task. This without relying on …

Nowadays, the need to efficiently process information in Internet of Things (IoT)-oriented
heterogeneous scenarios has increased significantly, eg, in all scenarios where unobtrusive …

TinyRCE is a hyperspherical classifier aimed at Continual Learning On-Tiny-Devices, a
challenging task in which a Machine Learning model is required to learn from continuous …