no code implementations • 30 May 2024 • Duhun Hwang, Suhyun Kang, Moonjung Eo, Jimyeong Kim, Wonjong Rhee
In the pursuit of this objective, average measure has been employed as the prevalent measure for evaluating models and comparing algorithms in the existing DG studies.
no code implementations • 11 Jan 2024 • Jaeill Kim, Duhun Hwang, Eunjung Lee, Jangwon Suh, Jimyeong Kim, Wonjong Rhee
In the past few years, contrastive learning has played a central role for the success of visual unsupervised representation learning.
1 code implementation • CVPR 2023 • Jaeill Kim, Suhyun Kang, Duhun Hwang, Jungwook Shin, Wonjong Rhee
Since the introduction of deep learning, a wide scope of representation properties, such as decorrelation, whitening, disentanglement, rank, isotropy, and mutual information, have been studied to improve the quality of representation.
Ranked #18 on Domain Generalization on TerraIncognita
1 code implementation • CVPR 2023 • Suhyun Kang, Duhun Hwang, Moonjung Eo, Taesup Kim, Wonjong Rhee
In this study, we propose Geometry-Adaptive Preconditioned gradient descent (GAP) that can overcome the limitations in MAML; GAP can efficiently meta-learn a preconditioner that is dependent on task-specific parameters, and its preconditioner can be shown to be a Riemannian metric.
no code implementations • ICML Workshop AML 2021 • Duhun Hwang, Eunjung Lee, Wonjong Rhee
AID-purifier is an auxiliary network that works as an add-on to an already trained main classifier.
no code implementations • 8 Nov 2018 • Daeyoung Choi, Kyungeun Lee, Duhun Hwang, Wonjong Rhee
In this study, the effects of eight representation regularization methods are investigated, including two newly developed rank regularizers (RR).