most citedA Continual and Incremental Learning Approach for TinyML On-device Training Using Dataset Distillation and Model Size Adaption

8 citations · 12 across the 3 of their papers we have counts for

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cs.LG2024★ 8 cited

A Continual and Incremental Learning Approach for TinyML On-device Training Using Dataset Distillation and Model Size Adaption

Marcus Rüb, Philipp Tuchel, Axel Sikora +1

A new algorithm for incremental learning in the context of Tiny Machine learning (TinyML) is presented, which is optimized for low-performance and energy efficient embedded devices…

cs.LG2023★ 1 cited

TinyProp -- Adaptive Sparse Backpropagation for Efficient TinyML On-device Learning

Marcus Rüb, Daniel Maier, Daniel Mueller-Gritschneder +1

Training deep neural networks using backpropagation is very memory and computationally intensive. This makes it difficult to run on-device learning or fine-tune neural networks on…