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Hyeong Gwon Hong
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2020 – today
- 2024
- [c9]Hyeong Gwon Hong, Yooshin Cho, Hanbyel Cho, Jaesung Ahn, Junmo Kim:
Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective. AAAI 2024: 12473-12481 - 2023
- [c8]Yooshin Cho, Hanbyel Cho, Hyeong Gwon Hong, Jaesung Ahn, Dongmin Cho, JungWoo Chang, Junmo Kim:
Localization using Multi-Focal Spatial Attention for Masked Face Recognition. FG 2023: 1-6 - [c7]Seunghee Koh, Hyounguk Shon, Janghyeon Lee, Hyeong Gwon Hong, Junmo Kim:
Disposable Transfer Learning for Selective Source Task Unlearning. ICCV 2023: 11718-11726 - [c6]Gyojin Han, Jaehyun Choi, Hyeong Gwon Hong, Junmo Kim:
Data Poisoning Attack Aiming the Vulnerability of Continual Learning. ICIP 2023: 1905-1909 - [i8]Yooshin Cho, Hanbyel Cho, Hyeong Gwon Hong, Jaesung Ahn, Dongmin Cho, JungWoo Chang, Junmo Kim:
Localization using Multi-Focal Spatial Attention for Masked Face Recognition. CoRR abs/2305.01905 (2023) - [i7]Seunghee Koh, Hyounguk Shon, Janghyeon Lee, Hyeong Gwon Hong, Junmo Kim:
Disposable Transfer Learning for Selective Source Task Unlearning. CoRR abs/2308.09971 (2023) - [i6]Hyeong Gwon Hong, Yooshin Cho, Hanbyel Cho, Jaesung Ahn, Junmo Kim:
Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective. CoRR abs/2312.12488 (2023) - 2022
- [c5]Seung Ho Na
, Hyeong Gwon Hong
, Junmo Kim
, Seungwon Shin
:
Closing the Loophole: Rethinking Reconstruction Attacks in Federated Learning from a Privacy Standpoint. ACSAC 2022: 332-345 - [c4]Yooshin Cho, Youngsoo Kim, Hanbyel Cho, Jaesung Ahn, Hyeong Gwon Hong, Junmo Kim:
Rethinking Efficacy of Softmax for Lightweight Non-local Neural Networks. ICIP 2022: 1031-1035 - [i5]Yooshin Cho, Youngsoo Kim, Hanbyel Cho, Jaesung Ahn, Hyeong Gwon Hong, Junmo Kim:
Rethinking Efficacy of Softmax for Lightweight Non-Local Neural Networks. CoRR abs/2207.13423 (2022) - [i4]Gyojin Han, Jaehyun Choi, Hyeong Gwon Hong, Junmo Kim:
Training Time Adversarial Attack Aiming the Vulnerability of Continual Learning. CoRR abs/2211.15875 (2022) - 2021
- [j1]Pyunghwan Ahn
, Hyeong Gwon Hong
, Junmo Kim
:
Differentiable Architecture Search Based on Coordinate Descent. IEEE Access 9: 48544-48554 (2021) - [c3]Byungju Kim, Hyeong Gwon Hong, Junmo Kim:
De-biasing Neural Networks with Estimated Offset for Class Imbalanced Learning. WACV 2021: 1478-1486 - 2020
- [c2]Janghyeon Lee, Donggyu Joo, Hyeong Gwon Hong, Junmo Kim:
Residual Continual Learning. AAAI 2020: 4553-4560 - [c1]Janghyeon Lee, Hyeong Gwon Hong, Donggyu Joo, Junmo Kim:
Continual Learning With Extended Kronecker-Factored Approximate Curvature. CVPR 2020: 8998-9007 - [i3]Janghyeon Lee, Donggyu Joo, Hyeong Gwon Hong, Junmo Kim:
Residual Continual Learning. CoRR abs/2002.06774 (2020) - [i2]Janghyeon Lee, Hyeong Gwon Hong, Donggyu Joo, Junmo Kim:
Continual Learning with Extended Kronecker-factored Approximate Curvature. CoRR abs/2004.07507 (2020)
2010 – 2019
- 2019
- [i1]Hyeong Gwon Hong, Pyunghwan Ahn, Junmo Kim:
EDAS: Efficient and Differentiable Architecture Search. CoRR abs/1912.01237 (2019)
Coauthor Index
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