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1
A k-populations algorithm for clustering categorical data

Kim, DW; Lee, K; Lee, Doheon; Lee, Kwang-Hyung, PATTERN RECOGNITION, v.38, pp.1131 - 1134, 2005-07

2
A kernel-based subtractive clustering method

Kim, DW; Lee, K; Lee, Doheon; Lee, Kwang-Hyung, PATTERN RECOGNITION LETTERS, v.26, pp.879 - 891, 2005-05

3
Dynamic functional connectivity analysis using transition-point time-window and clustering with optimized number of clusters in fMRI study = 뇌 상태 전환 시점 탐지 및 개수 최적화 클러스터링 기반 역동적인 기능적 뇌 연결성 분석방법link

Lee, Young-Beom; 이영범; et al, 한국과학기술원, 2017

4
Enabling large-scale Bayesian network learning by preserving intercluster directionality

Jung, S; Lee, Kwang-Hyung; Lee, Doheon, IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E90D, pp.1018 - 1027, 2007-07

5
Evaluation of the performance of clustering algorithms in kernel-induced feature space

Kim, DW; Lee, KY; Lee, Doheon; Lee, Kwang-Hyung, PATTERN RECOGNITION, v.38, pp.607 - 611, 2005-04

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