Adaptive Principal Surfaces
提出一种主成分分析的非线性推广方法，利用MARS过程的思想自适应构建数据的主曲面，可用于曲线曲面重建和数据摘要。
We develop a nonlinear generalization of principal components analysis. A principal surface of the data is constructed adaptively, using some ideas from the MARS procedure of Friedman. We explore applications to curve and surface reconstruction and to data summarization.