@inproceedings{a7b7eed6148b4296afb7e489395cc381,
title = "Geometric models with co-occurrence groups",
abstract = "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.",
author = "Joan Bruna and St{\'e}phane Mallat",
year = "2010",
language = "English (US)",
isbn = "2930307102",
series = "Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, ESANN 2010",
pages = "259--264",
booktitle = "Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, ESANN 2010",
note = "18th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2010 ; Conference date: 28-04-2010 Through 30-04-2010",
}