Learning transformations for clustering and classification

  title={Learning transformations for clustering and classification},
  author={Qiang Qiu and Guillermo Sapiro},
  journal={Journal of Machine Learning Research},
A low-rank transformation learning framework for subspace clustering and classification is here proposed. Many high-dimensional data, such as face images and motion sequences, approximately lie in a union of low-dimensional subspaces. The corresponding subspace clustering problem has been extensively studied in the literature to partition such… CONTINUE READING