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
An FPGA-Based Accelerator for Graph Embedding using Sequential Training Algorithm
Kazuki Sunaga, Keisuke Sugiura, Hiroki Matsutani
A graph embedding is an emerging approach that can represent a graph structure with a fixed-length low-dimensional vector. node2vec is a well-known algorithm to obtain such a graph…