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 decreasing.java

/** * First attempt to look at difference signal. LocalMax and Min will * proboably be rewritten after this. * * @author Waleed Kadous * @version $Id: Decreasing.java,v 1.1.1.1 2002/06/28
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java lineevent.java

package tclass.pep; import tclass.*; import tclass.util.*; import java.util.*; public class LineEvent implements EventI { Segment source; float avg; float midTime; float grad
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java increasing.java

/** * First attempt to look at difference signal. LocalMax and Min will * proboably be rewritten after this. * * @author Waleed Kadous * @version $Id: Increasing.java,v 1.1.1.1 2002/06/28
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java gradienttheme.java

package com.incors.plaf.kunststoff; /* * This code was developed by INCORS GmbH (www.incors.com). * It is published under the terms of the GNU Lesser General Public License. */ import java.awt.*;
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java kunststoffscrollbarui.java

package com.incors.plaf.kunststoff; /* * This code was developed by INCORS GmbH (www.incors.com). * It is published under the terms of the GNU Lesser General Public License. */ import java.awt.*;
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cs form1.cs

namespace WinTestControl { using System; using System.Drawing; using System.Collections; using System.ComponentModel; using System.WinForms; using System.Data; using W
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java plafres_th.java

/****************************************************************************** * The contents of this file are subject to the Compiere License Version 1.1 * ("License"); You may not use this f
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java plafres.java

/****************************************************************************** * The contents of this file are subject to the Compiere License Version 1.1 * ("License"); You may not use this f
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java plafres_fr.java

/****************************************************************************** * The contents of this file are subject to the Compiere License Version 1.1 * ("License"); You may not use this f
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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