@inproceedings{1879c1e073d543008ec52f291e2d80e6,
title = "Spline embedding for nonlinear dimensionality reduction",
abstract = "This paper presents a new algorithm for nonlinear dimensionality reduction (NLDR). Smoothing splines are used to map the locally-coordinatized data points into a single global coordinate system of lower dimensionality. In this work setting, we can achieve two goals. First, a global embedding is obtained by minimizing the low-dimensional coordinate reconstruction error. Second, the NLDR algorithm can be naturally extended to deal with out-of-sample data points. Experimental results illustrate the validity of our method.",
author = "Shiming Xiang and Feiping Nie and Changshui Zhang and Chunxia Zhang",
year = "2006",
doi = "10.1007/11871842_85",
language = "英语",
isbn = "354045375X",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "825--832",
booktitle = "Machine Learning",
note = "17th European Conference on Machine Learning, ECML 2006 ; Conference date: 18-09-2006 Through 22-09-2006",
}