代码搜索：Gradient

找到约 2,951 项符合「Gradient」的源代码

代码结果 2,951
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java gradienticon.java

// GradientIcon.java // GradientIcon is an Icon implementation that draws a 16 x 16 // gradient from startColor to endColor. package com.deitel.advjhtp1.drawing; // Java core packages import ja
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www.eeworm.com/read/394381/8227788

m nlconst.m

function [x,FVAL,lambda_out,EXITFLAG,OUTPUT,GRADIENT,HESS]= ... nlconst(funfcn,x,lb,ub,Ain,Bin,Aeq,Beq,confcn,OPTIONS,... verbosity,gradflag,gradconstflag,hessflag,meritFunctionType,... C
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www.eeworm.com/read/334860/12568224

m nlconst.m

function [x,FVAL,lambda_out,EXITFLAG,OUTPUT,GRADIENT,HESS]= ... nlconst(funfcn,x,lb,ub,Ain,Bin,Aeq,Beq,confcn,OPTIONS,... verbosity,gradflag,gradconstflag,hessflag,meritFunctionType,... C
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www.eeworm.com/read/111595/15509503

java cuboid.java

import java.awt.*; public class cuboid{ public double x, y, z; private int type; public int width, length, height, distanceToGround, distanceToCentre; public vector centre, normal, gradient
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www.eeworm.com/read/216626/4889466

bas_fun triangle.dg.3.bas_fun

10 2 0 0.0 0.0 3 0 0 0 ./triangle.DG.3.bas_fun.so phi_1 gradient_phi_1 2 0 1.0 0.0 3 0 0 0 ./triangle.DG.3.bas_fun.so phi_2 gradient_phi_2 2 0 0.0 1.0 3 0 0 0 ./triangle.DG.3.bas_fun.so phi_3 gr
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www.eeworm.com/read/216626/4889472

bas_fun triangle.dg.2.bas_fun

6 2 0 0.0 0.0 2 0 0 0 ./triangle.DG.2.bas_fun.so phi_1 gradient_phi_1 2 0 1.0 0.0 2 0 0 0 ./triangle.DG.2.bas_fun.so phi_2 gradient_phi_2 2 0 0.0 1.0 2 0 0 0 ./triangle.DG.2.bas_fun.so phi_3 gra
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www.eeworm.com/read/289743/8529932

m hill_obj.m

function [f,df]=hill_obj(x,dims,ii,dd,pars); % % computes the objective function and gradient of the non-convex formulation of MVU. % % copyright by Kilian Q. Weinberger, 2006 % % % % This file is
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www.eeworm.com/read/289487/8548520

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/387560/8665147

m os_asums.m

function Asums = os_asums(Gt, ci, nb, nsubset) %function Asums = os_asums(Gt, ci, nb, nsubset) % % for ordered subsets (block iterative, incremental gradient) algorithms, % we need to precompute the
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www.eeworm.com/read/428269/8880197

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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