1 research outputs found
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.Comment: 6 pages, ESANN 201