Nonlinear Nonnegative Component Analysis

  title={Nonlinear Nonnegative Component Analysis},
  author={Stefanos Zafeiriou and Maria Petrou},
  journal={2009 IEEE Conference on Computer Vision and Pattern Recognition},
In this paper general solutions for nonlinear nonnegative component analysis for data representation and recognition are proposed. That is, motivated by a combination of the Nonnegative Matrix Factorization (NMF) algorithm and kernel theory, which has lead to an NMF algorithm in a polynomial feature space, we propose a general framework where one can build a nonlinear nonnegative component analysis using kernels, the so-called projected gradient Kernel Nonnegative Matrix Factorization (PGKNMF… CONTINUE READING