3 papers
cs.LG2023
Disposable Transfer Learning for Selective Source Task Unlearning
Seunghee Koh, Hyounguk Shon, Janghyeon Lee +2
Transfer learning is widely used for training deep neural networks (DNN) for building a powerful representation. Even after the pre-trained model is adapted for the target task, th…
cs.CV2023
Lightweight Monocular Depth Estimation via Token-Sharing Transformer
Dong-Jae Lee, Jae Young Lee, Hyounguk Shon +4
Depth estimation is an important task in various robotics systems and applications. In mobile robotics systems, monocular depth estimation is desirable since a single RGB camera ca…
cs.LG2022
DLCFT: Deep Linear Continual Fine-Tuning for General Incremental Learning
Hyounguk Shon, Janghyeon Lee, Seung Hwan Kim +1
Pre-trained representation is one of the key elements in the success of modern deep learning. However, existing works on continual learning methods have mostly focused on learning…