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pro vyhledávání: '"Lee, Youngbin"'
Recommender systems can be helpful for individuals to make well-informed decisions in complex financial markets. While many studies have focused on predicting stock prices, even advanced models fall short of accurately forecasting them. Additionally,
Externí odkaz:
http://arxiv.org/abs/2404.07223
This paper explores the utilization of Temporal Graph Networks (TGN) for financial anomaly detection, a pressing need in the era of fintech and digitized financial transactions. We present a comprehensive framework that leverages TGN, capable of capt
Externí odkaz:
http://arxiv.org/abs/2404.00060
Recommender systems have been actively studied and applied in various domains to deal with information overload. Although there are numerous studies on recommender systems for movies, music, and e-commerce, comparatively less attention has been paid
Externí odkaz:
http://arxiv.org/abs/2403.18305
Recommender systems, crucial for user engagement on platforms like e-commerce and streaming services, often lag behind users' evolving preferences due to static data reliance. After Temporal Graph Networks (TGNs) were proposed, various studies have s
Externí odkaz:
http://arxiv.org/abs/2403.16066
Recommender systems have become essential tools for enhancing user experiences across various domains. While extensive research has been conducted on recommender systems for movies, music, and e-commerce, the rapidly growing and economically signific
Externí odkaz:
http://arxiv.org/abs/2306.10053
Autor:
Lee, Youngbin
Fibers are ubiquitous as elements in broad fields from conventional textiles and optics to smart textiles and electronics. One of the fiber fabrication methods, thermal drawing process, has a unique strength on a scalable production of multimaterial
Externí odkaz:
https://hdl.handle.net/1721.1/152011
Autor:
Lee, Youngbin, Lee, Jeong Hee, Lee, Dongwook, Oh, Sion, Park, Jongwook, Im, Kyungmin, Yoo, Sung Jong, Kim, Jinsoo
Publikováno v:
In Chemical Engineering Journal 15 November 2024 500
Publikováno v:
In Engineering Applications of Artificial Intelligence November 2024 137 Part B
Akademický článek
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Autor:
Wu, Yang, Ruan, Xuezhong, Chen, Chih-Hsin, Shin, Young Jun, Lee, Youngbin, Niu, Jing, Liu, Jingbo, Chen, Yuanfu, Yang, Kun-Lin, Zhang, Xinhai, Ahn, Jong-Hyun, Yang, Hyunsoo
Publikováno v:
Optics Express 21, 21395 (2013)
Due to its high electrical conductivity and excellent transmittance at terahertz frequencies, graphene is a promising candidate as transparent electrodes for terahertz devices. We demonstrate a liquid crystal based terahertz phase shifter with the gr
Externí odkaz:
http://arxiv.org/abs/1309.1595