Isabelle Guyon, N. Matic, and V. Vapnik
We present a method for discovering informative patterns from data. With this method, large databases can be reduced to only a few representative data entries. Our framework encompasses also methods for cleaning databases containing corrupted data. Both on-line and off-line algorithms are proposed and experimentally checked on databases of handwritten images. The generality of the framework makes it an attractive candidate for new applications in knowledge discovery.