Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Kim, Jooeun"'
Autor:
Kim, Jooeun, Kim, Jinri, Yeo, Kwangeun, Kim, Eungi, On, Kyoung-Woon, Mun, Jonghwan, Lee, Joonseok
Cold-start item recommendation is a long-standing challenge in recommendation systems. A common remedy is to use a content-based approach, but rich information from raw contents in various forms has not been fully utilized. In this paper, we propose
Externí odkaz:
http://arxiv.org/abs/2404.13808
Zero-shot learning offers an efficient solution for a machine learning model to treat unseen categories, avoiding exhaustive data collection. Zero-shot Sketch-based Image Retrieval (ZS-SBIR) simulates real-world scenarios where it is hard and costly
Externí odkaz:
http://arxiv.org/abs/2401.04860
Publikováno v:
In Nutrition March 2025 131
While many real-world data streams imply that they change frequently in a nonstationary way, most of deep learning methods optimize neural networks on training data, and this leads to severe performance degradation when dataset shift happens. However
Externí odkaz:
http://arxiv.org/abs/2107.00191
Publikováno v:
ACM International Conference Proceeding Series; 2/20/2019, p46-50, 5p
Autor:
Kim, Jooeun
Publikováno v:
The SAIS Review of International Affairs; March 2019, Vol. 39 Issue: 2 p57-63, 7p
Publikováno v:
Applied Biological Chemistry; 4/29/2022, Vol. 65 Issue 1, p1-8, 8p
Publikováno v:
Pain & Central Nervous System Week; 9/13/2024, p1043-1043, 1p