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pro vyhledávání: '"Cho, Ikhyun"'
Machine unlearning (MUL) is an arising field in machine learning that seeks to erase the learned information of specific training data points from a trained model. Despite the recent active research in MUL within computer vision, the majority of work
Externí odkaz:
http://arxiv.org/abs/2403.09681
The precipitation nowcasting methods have been elaborated over the centuries because rain has a crucial impact on human life. Not only quantitative precipitation forecast (QPF) models and convolutional long short-term memory (ConvLSTM), but also vari
Externí odkaz:
http://arxiv.org/abs/2211.15046
Publikováno v:
In Automation in Construction September 2024 165
Autor:
Cho, Ikhyun, Kang, U
How can we efficiently compress a model while maintaining its performance? Knowledge Distillation (KD) is one of the widely known methods for model compression. In essence, KD trains a smaller student model based on a larger teacher model and tries t
Externí odkaz:
http://arxiv.org/abs/2009.14822
Publikováno v:
PLoS ONE. 4/18/2022, Vol. 17 Issue 4, p1-22. 22p.
Autor:
Cho, Ikhyun1 (AUTHOR), Kang, U1 (AUTHOR) ukang@snu.ac.kr
Publikováno v:
PLoS ONE. 2/18/2022, Vol. 17 Issue 2, p1-12. 12p.
Publikováno v:
Proceedings of the 2014 Conference Research in Adaptive & Convergent Systems; 10/5/2014, p359-361, 3p
Publikováno v:
Proceedings of the 2014 Conference Research in Adaptive & Convergent Systems; 10/5/2014, p215-217, 3p