1 citations · 2 across the 5 of their papers we have counts for
5 papers
Towards a Better Evaluation of Out-of-Domain Generalization
Duhun Hwang, Suhyun Kang, Moonjung Eo +2
The objective of Domain Generalization (DG) is to devise algorithms and models capable of achieving high performance on previously unseen test distributions. In the pursuit of this…
Enhancing Contrastive Learning with Efficient Combinatorial Positive Pairing
Jaeill Kim, Duhun Hwang, Eunjung Lee +3
In the past few years, contrastive learning has played a central role for the success of visual unsupervised representation learning. Around the same time, high-performance non-con…
VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution
Jaeill Kim, Suhyun Kang, Duhun Hwang +2
Since the introduction of deep learning, a wide scope of representation properties, such as decorrelation, whitening, disentanglement, rank, isotropy, and mutual information, have…
Meta-Learning with a Geometry-Adaptive Preconditioner
Suhyun Kang, Duhun Hwang, Moonjung Eo +2
Model-agnostic meta-learning (MAML) is one of the most successful meta-learning algorithms. It has a bi-level optimization structure where the outer-loop process learns a shared in…
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense
Duhun Hwang, Eunjung Lee, Wonjong Rhee
We propose an AID-purifier that can boost the robustness of adversarially-trained networks by purifying their inputs. AID-purifier is an auxiliary network that works as an add-on t…