Search Results for author: DoGuk Kim

Found 2 papers, 1 papers with code

SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness

1 code implementation NeurIPS 2021 Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, DoGuk Kim, Jinwoo Shin

Randomized smoothing is currently a state-of-the-art method to construct a certifiably robust classifier from neural networks against $\ell_2$-adversarial perturbations.

SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Adversarial Robustness

no code implementations ICML Workshop AML 2021 Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, DoGuk Kim, Jinwoo Shin

Randomized smoothing is currently a state-of-the-art method to construct a certifiably robust classifier from neural networks against $\ell_2$-adversarial perturbations.

Adversarial Robustness

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