Papers Published

1. Pu, Y; Yuan, X; Carin, L, A generative model for deep convolutional learning, 3rd International Conference on Learning Representations, ICLR 2015 - Workshop Track Proceedings (January, 2015) .
   (last updated on 2024/12/31)

   Abstract:
   © 2015 International Conference on Learning Representations, ICLR. All rights reserved. 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.