Nico Migenda, Ralf Möller 0002, Wolfram Schenck. Adaptive local Principal Component Analysis improves the clustering of high-dimensional data. Pattern Recognition, 146:110030, February 2024. [doi]
@article{MigendaMS24,
title = {Adaptive local Principal Component Analysis improves the clustering of high-dimensional data},
author = {Nico Migenda and Ralf Möller 0002 and Wolfram Schenck},
year = {2024},
month = {February},
doi = {10.1016/j.patcog.2023.110030},
url = {https://doi.org/10.1016/j.patcog.2023.110030},
researchr = {https://researchr.org/publication/MigendaMS24},
cites = {0},
citedby = {0},
journal = {Pattern Recognition},
volume = {146},
pages = {110030},
}