A generative model for deep convolutional learning

Yunchen Pu, Xin Yuan, Lawrence Carin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

A generative model is developed for deep (multi-layered) convolutional dictionary learning. A novel probabilistic pooling operation is integrated into the deep model, yielding efficient bottom-up (pretraining) and top-down (refinement) probabilistic learning. Experimental results demonstrate powerful capabilities of the model to learn multi-layer features from images, and excellent classification results are obtained on the MNIST and Caltech 101 datasets.
Original languageEnglish (US)
Title of host publication3rd International Conference on Learning Representations, ICLR 2015 - Workshop Track Proceedings
PublisherInternational Conference on Learning Representations, ICLR
StatePublished - Jan 1 2015
Externally publishedYes

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