8 citations · 11 across the 2 of their papers we have counts for
2 papers
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.LG2024★ 3 cited
Advancing On-Device Neural Network Training with TinyPropv2: Dynamic, Sparse, and Efficient Backpropagation
Marcus Rüb, Axel Sikora, Daniel Mueller-Gritschneder
This study introduces TinyPropv2, an innovative algorithm optimized for on-device learning in deep neural networks, specifically designed for low-power microcontroller units. TinyP…