代码搜索：Gradient

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m contents.m

% Pre-image problem for RBF kernel. % % rbfpreimg - Schoelkopf's fixed-point algorithm. % rbfpreimg2 - Gradient optimization. % rbfpreimg3 - Kwok-Tsang's algorithm. % % About: Statistical Pattern
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www.eeworm.com/read/220289/14843797

m rbfbkp.m

function g = rbfbkp(net, x, z, n2, deltas) %RBFBKP Backpropagate gradient of error function for RBF network. % % Description % G = RBFBKP(NET, X, Z, N2, DELTAS) takes a network data structure NET % to
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www.eeworm.com/read/215705/15051973

m compgrad.m

% Compute gradient relative to weights for subnet=1:ninputs for column=1:ninputs grad12{subnet}(:,column) = sum(jback2i{subnet,column},2); grad23{subnet}(:,1:nhidden) = grad23{sub
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www.eeworm.com/read/213492/15133712

m contents.m

% Pre-image problem for RBF kernel. % % rbfpreimg - Schoelkopf's fixed-point algorithm. % rbfpreimg2 - Gradient optimization. % rbfpreimg3 - Kwok-Tsang's algorithm. % % About: Statistical Pattern
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www.eeworm.com/read/212307/15160104

m rbfbkp.m

function g = rbfbkp(net, x, z, n2, deltas) %RBFBKP Backpropagate gradient of error function for RBF network. % % Description % G = RBFBKP(NET, X, Z, N2, DELTAS) takes a network data structure NET % to
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www.eeworm.com/read/13871/284580

m rbfbkp.m

function g = rbfbkp(net, x, z, n2, deltas) %RBFBKP Backpropagate gradient of error function for RBF network. % % Description % G = RBFBKP(NET, X, Z, N2, DELTAS) takes a network data structure NET
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www.eeworm.com/read/13911/287168

m gradlbfixed.m

function [grad] = gradlbfixed(Sigma,indsup,Alpsup,w0,C,Xapp,yapp,pow); %GRADLBFIXED Computes the gradient of an upper bound on SVM loss wrt SIGMA^POW % GRAD = GRADLBFIXED(SIGMA,INDSUP,ALPSUP,W0,C,X
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hard blue border

GradientGlow 1466201192 0.15 inches 1145661030 0.000 1332765556 100.000 1181491232 1 1196582244 Gradient: 2/0.000 0 3 1 0 0 255 255 0 0.500/1.000 0 3 1 0 0 255 255 0 0.500
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www.eeworm.com/read/175689/5343543

m contents.m

% Pre-image problem for RBF kernel. % % rbfpreimg - Schoelkopf's fixed-point algorithm. % rbfpreimg2 - Gradient optimization. % rbfpreimg3 - Kwok-Tsang's algorithm. % % About: Statistical Pattern
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www.eeworm.com/read/344585/3207719

m rbfbkp.m

function g = rbfbkp(net, x, z, n2, deltas) %RBFBKP Backpropagate gradient of error function for RBF network. % % Description % G = RBFBKP(NET, X, Z, N2, DELTAS) takes a network data structure NET % to
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