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Sukmin Yun
Sukmin Yun
Ph.D. Student, KAIST
Verified email at kaist.ac.kr
Title
Cited by
Cited by
Year
Regularizing class-wise predictions via self-knowledge distillation
S Yun, J Park, K Lee, J Shin
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
1122020
Robust inference via generative classifiers for handling noisy labels
K Lee, S Yun, K Lee, H Lee, B Li, J Shin
International Conference on Machine Learning, 3763-3772, 2019
612019
Opencos: Contrastive semi-supervised learning for handling open-set unlabeled data
J Park, S Yun, J Jeong, J Shin
arXiv preprint arXiv:2107.08943, 2021
72021
Robust determinantal generative classifier for noisy labels and adversarial attacks
K Lee, S Yun, K Lee, H Lee, B Li, J Shin
42018
Time Is MattEr: Temporal Self-supervision for Video Transformers
S Yun, J Kim, D Han, H Song, JW Ha, J Shin
arXiv preprint arXiv:2207.09067, 2022
2022
TSPipe: Learn from Teacher Faster with Pipelines
H Lim, Y Kim, S Yun, J Shin, D Han
International Conference on Machine Learning, 13302-13312, 2022
2022
Patch-Level Representation Learning for Self-Supervised Vision Transformers
S Yun, H Lee, J Kim, J Shin
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
2022
PASS: Patch-Aware Self-Supervision for Vision Transformer
S Yun, H Lee, J Kim, J Shin
2021
Regularizing Predictions via Class-wise Self-knowledge Distillation
S Yun, J Park, K Lee, J Shin
2019
Deep determinantal generative classifier: robustness on noisy and adversarial samples
K Lee, S Yun, K Lee, H Lee, B Li, J Shin
2019
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Articles 1–10