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This project forked from jackculpepper/sparsenet-starter-kit
Sparsenet starter kit! Author: Jack Culpepper License: BSD checkgrad.m was written by Carl Rasmussen sfigure.m was written by Daniel Eaton This program is related to the paper by Bruno and David: B. A. Olshausen and D. J. Field. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381(6583):607-9, jun 1996. (Bruno is my PhD advisor.) Assumes: IMAGES.mat is in ../data/IMAGES.mat lbfgsb-stewart is in ../lbfgsb-stewart To get started: - Run unittest in matlab. - Use ~jack/bin/gqview to look in the state dir. To run positive only coefficients: - Comment out this line in unittest.m: nb = zeros(1,M); % bound type (none) For a new dataset: - Add a case to the switch statement. For a new optimization procedure: - Add a case to the switch statement. For a new model: - Write a check and objfun for a new inference objfun. - Write a check and objfun for a new learning objfun.
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