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Searched
refs:Methods
(Results
26 - 38
of
38
) sorted by null
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/external/antlr/antlr-3.4/runtime/Delphi/Sources/Antlr3.Runtime/
Antlr.Runtime.Tools.pas
123
{
Methods
}
140
{
Methods
}
193
{
Methods
}
Antlr.Runtime.Collections.pas
58
{
Methods
}
Antlr.Runtime.pas
66
{
Methods
}
195
{
Methods
}
294
{
Methods
}
320
{
Methods
}
395
{
Methods
}
418
{
Methods
}
439
{
Methods
}
590
/// The goal of all lexer rules/
methods
is to create a token object.
640
{
Methods
}
701
{
Methods
}
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/external/clang/lib/Serialization/
ASTWriter.cpp
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ASTReader.cpp
434
// Load instance
methods
441
// Load factory
methods
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/external/clang/lib/AST/
VTableBuilder.cpp
176
const OverridingMethods&
Methods
= I->second;
178
for (OverridingMethods::const_iterator I =
Methods
.begin(),
179
E =
Methods
.end(); I != E; ++I) {
444
/// Offsets - Keeps track of
methods
and their offsets.
479
// relationship between the two
methods
.
500
// The
methods
must have the same name.
600
///
Methods
for iterating over the components.
861
/// MethodInfoMap - The information for all
methods
in the vtable we're
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/external/antlr/antlr-3.4/runtime/CSharp2/Sources/Antlr3.Runtime.Tests/
ITreeNodeStreamFixture.cs
630
#region Helper
Methods
/external/clang/lib/Rewrite/Frontend/
RewriteModernObjC.cpp
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/external/clang/lib/Sema/
SemaDeclCXX.cpp
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/external/ceres-solver/docs/
solving.tex
5
\section{Trust Region
Methods
}
77
For all but the smallest problems the solution of~\eqref{eq:simple} in each iteration of the Levenberg-Marquardt algorithm is the dominant computational cost in Ceres. Ceres provides a number of different options for solving~\eqref{eq:simple}. There are two major classes of
methods
- factorization and iterative.
79
The factorization
methods
are based on computing an exact solution of~\eqref{eq:lsqr} using a Cholesky or a QR factorization and lead to an exact step Levenberg-Marquardt algorithm. But it is not clear if an exact solution of~\eqref{eq:lsqr} is necessary at each step of the LM algorithm to solve~\eqref{eq:nonlinsq}. In fact, we have already seen evidence that this may not be the case, as~\eqref{eq:lsqr} is itself a regularized version of~\eqref{eq:linearapprox}. Indeed, it is possible to construct non-linear optimization algorithms in which the linearized problem is solved approximately. These algorithms are known as inexact Newton or truncated Newton
methods
~\cite{nocedal2000numerical}.
99
ourselves to moving along the direction of the gradient. Dogleg
methods
finds a vector $\Delta x$ defined by $\Delta
216
Recall that in both of the trust-region
methods
described above, the key computational cost is the solution of a linear least squares problem of the form
314
option: sparse direct
methods
. These
methods
store $S$ as a sparse
318
Sparse direct
methods
, depending on the exact sparsity structure of the Schur complement,
342
Equation~\eqref{eq:schurtrick1} is closely related to {\em Domain Decomposition
methods
} for solving large linear systems that arise in structural engineering and partial differential eq (…)
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/external/webkit/PerformanceTests/SunSpider/tests/sunspider-0.9/
string-unpack-code.js
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/external/webkit/PerformanceTests/SunSpider/tests/sunspider-0.9.1/
string-unpack-code.js
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/prebuilts/tools/common/m2/internal/com/google/code/findbugs/findbugs/2.0.1/
findbugs-2.0.1.jar
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