代码搜索：Gradient
找到约 2,951 项符合「Gradient」的源代码
代码结果 2,951
www.eeworm.com/read/157074/11741269
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
www.eeworm.com/read/153969/11997454
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
www.eeworm.com/read/256398/12001732
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
www.eeworm.com/read/340489/12152838
css style.css
body,td,th {
font-size: 9pt;
color: #dddddd;
}
a:link {
color: #dddddd;
}
a:visited {
color: #dddddd;
}
BODY {
filter:progid:DXImageTransform.Microsoft.gradient(startcolorstr=#FF0000
www.eeworm.com/read/253950/12173576
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
www.eeworm.com/read/253950/12173622
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
www.eeworm.com/read/339665/12211565
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
www.eeworm.com/read/339665/12211645
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
www.eeworm.com/read/150905/12250458
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
www.eeworm.com/read/150905/12250502
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