UFLDL,build deep network,vectorization,softmax,working with large images,pca

UFLDL作业上传\build deep networks作业\checkStackedAECost.m
.............\.......................\computeNumericalGradient.m
.............\.......................\feedForwardAutoencoder.m
.............\.......................\initializeParameters.m
.............\.......................\loadMNISTImages.m
.............\.......................\loadMNISTLabels.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
.............\.......................\params2stack.m
.............\.......................\softmaxCost.m
.............\.......................\softmaxTrain.m
.............\.......................\sparseAutoencoderCost.m
.............\.......................\stack2params.m
.............\.......................\stackedAECost.m
.............\.......................\stackedAEExercise.m
.............\.......................\stackedAEPredict.m
.............\ExerciseVectorization导师写\checkNumericalGradient.m
.............\...........................\computeNumericalGradient.m
.............\...........................\display_network.m
.............\...........................\initializeParameters.m
.............\...........................\loadMNISTImages.m
.............\...........................\loadMNISTLabels.m
.............\...........................\minFunc\ArmijoBacktrack.m

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