2 papers
cs.LG2024
Skip2-LoRA: A Lightweight On-device DNN Fine-tuning Method for Low-cost Edge Devices
Hiroki Matsutani, Masaaki Kondo, Kazuki Sunaga +1
This paper proposes Skip2-LoRA as a lightweight fine-tuning method for deep neural networks to address the gap between pre-trained and deployed models. In our approach, trainable L…
cs.LG2024
A Tiny Supervised ODL Core with Auto Data Pruning for Human Activity Recognition
Hiroki Matsutani, Radu Marculescu
In this paper, we introduce a low-cost and low-power tiny supervised on-device learning (ODL) core that can address the distributional shift of input data for human activity recogn…