A Generative Model for Deep Convolutional Learning

April 15, 2015 ยท Declared Dead ยท ๐Ÿ› International Conference on Learning Representations

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Authors Yunchen Pu, Xin Yuan, Lawrence Carin arXiv ID 1504.04054 Category stat.ML: Machine Learning (Stat) Cross-listed cs.LG, cs.NE Citations 4 Venue International Conference on Learning Representations Last Checked 5 months ago
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.
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