Adaptive Laplacian eigenfunctions as bases for regression analysis

Regression or least squares fitting is an important problem in statistics, data mining and many other applications. In recent years, basis functions derived from the underlying geometry of data, primarily Laplacian eigenfunctions, have attracted much interest. In this paper, we present a new framework based on adaptive Laplacian eigenfunctions and show the benefit of using a time-varying basis in regression analysis.

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Lei Ding, Xiaole Bai
• Keywords: Adaptive Laplacian Eigenfunctions, Basis Functions, Computer Vision, ICPR 2008, Laplacian Eigenfunctions