文件名称:Sparse-Autoencoder

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神经网络稀疏自编码器的实现;从给定的很多张自然图片中截取出大小为8*8的小patches图片共10000张,现在需要用sparse autoencoder的方法训练出一个隐含层网络所学习到的特征。-Sparse neural networks since implementation of the encoder interception of a size of 8* 8 picture small patches given a lot of sheets natural picture Chinese Communist 10000, now need to use sparse autoencoder way to train a hidden layer of the network to learn Characteristics.
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下载文件列表





Sparse Autoencoder\starter\checkNumericalGradient.m

..................\.......\computeNumericalGradient.m

..................\.......\display_network.m

..................\.......\IMAGES.mat

..................\.......\initializeParameters.m

..................\.......\minFunc\ArmijoBacktrack.m

..................\.......\.......\autoGrad.m

..................\.......\.......\autoHess.m

..................\.......\.......\autoHv.m

..................\.......\.......\autoTensor.m

..................\.......\.......\callOutput.m

..................\.......\.......\conjGrad.m

..................\.......\.......\dampedUpdate.m

..................\.......\.......\example_minFunc.m

..................\.......\.......\example_minFunc_LR.m

..................\.......\.......\isLegal.m

..................\.......\.......\lbfgs.m

..................\.......\.......\lbfgsC.c

..................\.......\.......\lbfgsC.mexa64

..................\.......\.......\lbfgsC.mexglx

..................\.......\.......\lbfgsC.mexmac

..................\.......\.......\lbfgsC.mexmaci

..................\.......\.......\lbfgsC.mexmaci64

..................\.......\.......\lbfgsC.mexw32

..................\.......\.......\lbfgsC.mexw64

..................\.......\.......\lbfgsUpdate.m

..................\.......\.......\.ogistic\LogisticDiagPrecond.m

..................\.......\.......\........\LogisticHv.m

..................\.......\.......\........\LogisticLoss.m

..................\.......\.......\........\mexutil.c

..................\.......\.......\........\mexutil.h

..................\.......\.......\........\mylogsumexp.m

..................\.......\.......\........\repmatC.c

..................\.......\.......\........\repmatC.dll

..................\.......\.......\........\repmatC.mexglx

..................\.......\.......\........\repmatC.mexmac

..................\.......\.......\mchol.m

..................\.......\.......\mcholC.c

..................\.......\.......\mcholC.mexmaci64

..................\.......\.......\mcholC.mexw32

..................\.......\.......\mcholC.mexw64

..................\.......\.......\mcholinc.m

..................\.......\.......\minFunc.m

..................\.......\.......\minFunc_processInputOptions.m

..................\.......\.......\polyinterp.m

..................\.......\.......\precondDiag.m

..................\.......\.......\precondTriu.m

..................\.......\.......\precondTriuDiag.m

..................\.......\.......\rosenbrock.m

..................\.......\.......\taylorModel.m

..................\.......\.......\WolfeLineSearch.m

..................\.......\sampleIMAGES.m

..................\.......\sparseAutoencoderCost.m

..................\.......\train.m

..................\.......\weights.jpg

..................\.......\minFunc\logistic

..................\.......\minFunc

..................\starter

Sparse Autoencoder

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