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Akademický článek

INSANet: INtra-INter Spectral Attention Network for Effective Feature Fusion of Multispectral Pedestrian Detection.

Autor: Lee, Sangin¹ (AUTHOR) silee@rcv.sejong.ac.kr, Kim, Taejoo² (AUTHOR) tjkim@rcv.sejong.ac.kr, Shin, Jeongmin² (AUTHOR) jmshin@rcv.sejong.ac.kr, Kim, Namil³ (AUTHOR) namil.kim@naverlabs.com, Choi, Yukyung² (AUTHOR) ykchoi@rcv.sejong.ac.kr

Publikováno v: Sensors (14248220). Feb2024, Vol. 24 Issue 4, p1168. 17p.

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A unified algorithm for the non-convex penalized estimation: The ncpen package

Autor: Kim, Dongshin, Lee, Sangin, Kwon, Sunghoon

Various R packages have been developed for the non-convex penalized estimation but they can only be applied to the smoothly clipped absolute deviation (SCAD) or minimax concave penalty (MCP). We develop an R package, entitled ncpen, for the non-conve

Externí odkaz: http://arxiv.org/abs/1811.05061

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Akademický článek

Identification of Terpene Compositions in the Leaves and Inflorescences of Hybrid Cannabis Species Using Headspace-Gas Chromatography/Mass Spectrometry.

Autor: Lee, Sangin¹ (AUTHOR) ahfqqhsi@naver.com, Kim, Eun Jae¹ (AUTHOR) dmswo3537@naver.com, Kwon, Eunjeong¹ (AUTHOR), Oh, Seo Jeong¹ (AUTHOR), Cho, Mansoo² (AUTHOR) chomansoo@gmail.com, Kim, Chul Min³ (AUTHOR) chulmin21@wku.ac.kr, Lee, Wonwoong⁴ (AUTHOR) wwlee@woosuk.ac.kr, Hong, Jongki¹ (AUTHOR) wwlee@woosuk.ac.kr

Publikováno v: Molecules. Dec2023, Vol. 28 Issue 24, p8082. 13p.

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Akademický článek

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Strong rules for nonconvex penalties and their implications for efficient algorithms in high-dimensional regression

Autor: Lee, Sangin, Breheny, Patrick

Publikováno v: Journal of Computational and Graphical Statistics, 24: 1074-1091 (2015)

We consider approaches for improving the efficiency of algorithms for fitting nonconvex penalized regression models such as SCAD and MCP in high dimensions. In particular, we develop rules for discarding variables during cyclic coordinate descent. Th

Externí odkaz: http://arxiv.org/abs/1403.2963

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