Geometric Models with Co-occurrence Groups
  A geometric model of sparse signal representations is introduced for classes of signals. It is computed by optimizing co-occurrence groups with a maximum likelihood estimate calculated with a Bernoulli mixture model. Applications to face image compression and MNIST digit classification illustrate the applicability of this model. 
Joan Bruna and St\'ephane Mallat
cs.CV cs.IT math.IT