代码搜索：Gradient

找到约 2,951 项符合「Gradient」的源代码

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m olgd.m

function [net, options, errlog, pointlog] = olgd(net, options, x, t) %OLGD On-line gradient descent optimization. % % Description % [NET, OPTIONS, ERRLOG, POINTLOG] = OLGD(NET, OPTIONS, X, T) uses on
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m gpgrad.m

function g = gpgrad(net, x, t) %GPGRAD Evaluate error gradient for Gaussian Process. % % Description % G = GPGRAD(NET, X, T) takes a Gaussian Process data structure NET % together with a matrix X of
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m glmgrad.m

function [g, gdata, gprior] = glmgrad(net, x, t) %GLMGRAD Evaluate gradient of error function for generalized linear model. % % Description % G = GLMGRAD(NET, X, T) takes a generalized linear model da
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www.eeworm.com/read/396844/2407027

m maximize_params.m

function CPD = maximize_params(CPD, temp) % MAXIMIZE_PARAMS Find ML params of an MLP using Scaled Conjugated Gradient (SCG) % CPD = maximize_params(CPD, temperature) % temperature parameter is igno
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www.eeworm.com/read/393163/2487838

m mixexp_graddesc.m

%%%%%%%%%% function [theta, eta] = mixture_of_experts(q, data, num_iter, theta, eta) % MIXTURE_OF_EXPERTS Fit a piecewise linear regression model using stochastic gradient descent. % [theta, eta] =
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www.eeworm.com/read/393163/2488217

m maximize_params.m

function CPD = maximize_params(CPD, temp) % MAXIMIZE_PARAMS Find ML params of an MLP using Scaled Conjugated Gradient (SCG) % CPD = maximize_params(CPD, temperature) % temperature parameter is igno
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m gradlfixed.m

function [grad] = gradlfixed(Sigma,indsup,Alpsup,C,Xapp,yapp,pow); %GRADLFIXED Computes the gradient of an upper bound on SVM loss wrt SIGMA^POW % GRAD = GRADLFIXED(SIGMA,INDSUP,ALPSUP,C,XAPP,YAPP,
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www.eeworm.com/read/369958/2788112

m gradwfixed.m

function [grad] = gradwfixed(Sigma,indsup,Alpsup,C,Xapp,yapp,Sigmaold,pow); %GRADWFIXED Computes the gradient of an upper bound on SVM loss wrt SIGMA^POW % GRAD = GRADWFIXED(SIGMA,INDSUP,ALPSUP,C,X
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www.eeworm.com/read/359369/2978470

m olgd.m

function [net, options, errlog, pointlog] = olgd(net, options, x, t) %OLGD On-line gradient descent optimization. % % Description % [NET, OPTIONS, ERRLOG, POINTLOG] = OLGD(NET, OPTIONS, X, T) uses
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www.eeworm.com/read/359369/2978542

m rbfgrad.m

function [g, gdata, gprior] = rbfgrad(net, x, t) %RBFGRAD Evaluate gradient of error function for RBF network. % % Description % G = RBFGRAD(NET, X, T) takes a network data structure NET together
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