8 citations · 12 across the 2 of their papers we have counts for
5 papers
Training GANs with Stronger Augmentations via Contrastive Discriminator
Jongheon Jeong, Jinwoo Shin
Recent works in Generative Adversarial Networks (GANs) are actively revisiting various data augmentation techniques as an effective way to prevent discriminator overfitting. It is…
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances
Jihoon Tack, Sangwoo Mo, Jongheon Jeong +1
Novelty detection, i.e., identifying whether a given sample is drawn from outside the training distribution, is essential for reliable machine learning. To this end, there have bee…
Consistency Regularization for Certified Robustness of Smoothed Classifiers
Jongheon Jeong, Jinwoo Shin
A recent technique of randomized smoothing has shown that the worst-case (adversarial) -robustness can be transformed into the average-case Gaussian-robustness by "smoothin…
M2m: Imbalanced Classification via Major-to-minor Translation
Jaehyung Kim, Jongheon Jeong, Jinwoo Shin
In most real-world scenarios, labeled training datasets are highly class-imbalanced, where deep neural networks suffer from generalizing to a balanced testing criterion. In this pa…
Training CNNs with Selective Allocation of Channels
Jongheon Jeong, Jinwoo Shin
Recent progress in deep convolutional neural networks (CNNs) have enabled a simple paradigm of architecture design: larger models typically achieve better accuracy. Due to this, in…