Hyeong Gwon Hong

Continual Learning With Extended Kronecker-Factored Approximate Curvature

Junmo Kim, Janghyeon Lee, Hyeong Gwon Hong, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

EDAS: Efficient and Differentiable Architecture Search pdf

Junmo Kim, Hyeong Gwon Hong, Pyunghwan Ahn, 2019, ArXiv.

Residual Continual Learning

Junmo Kim, Janghyeon Lee, Hyeong Gwon Hong, 2020, AAAI.

De-biasing Neural Networks with Estimated Offset for Class Imbalanced Learning

Junmo Kim, Hyeong Gwon Hong, Byungju Kim, 2021, 2021 IEEE Winter Conference on Applications of Computer Vision (WACV).

Differentiable Architecture Search Based on Coordinate Descent

Junmo Kim, Hyeong Gwon Hong, Pyunghwan Ahn, 2021, IEEE Access.

Rethinking Efficacy of Softmax for Lightweight Non-Local Neural Networks

Hyeong Gwon Hong, Junmo Kim, Yooshin Cho, 2022, 2022 IEEE International Conference on Image Processing (ICIP).

Training Time Adversarial Attack Aiming the Vulnerability of Continual Learning

Hyeong Gwon Hong, Junmo Kim, Jaehyun Choi, 2022, ArXiv.

Closing the Loophole: Rethinking Reconstruction Attacks in Federated Learning from a Privacy Standpoint

Hyeong Gwon Hong, Seung Ho Na, Junmo Kim, 2022, ACSAC.

Data Poisoning Attack Aiming the Vulnerability of Continual Learning

Hyeong Gwon Hong, Junmo Kim, Jaehyun Choi, 2022, 2211.15875.

Disposable Transfer Learning for Selective Source Task Unlearning

Hyeong Gwon Hong, Junmo Kim, Janghyeon Lee, 2023, arXiv.org.