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  /external/valgrind/main/memcheck/tests/
wrap2.stdout.exp 0 computing fact(5)
wrap3.stdout.exp 0 computing fact1(5)
wrap8.stdout.exp 0 computing fact1(15)
wrap4.stdout.exp 0 computing fact1(5)
wrap5.stdout.exp 0 computing fact1(7)
  /external/valgrind/main/cachegrind/tests/
wrap5.stdout.exp 0 computing fact1(7)
  /external/ceres-solver/docs/
helloworld.tex 13 When solving a problem with Ceres, the first thing to do is to define a subclass of \texttt{CostFunction}. It is responsible for computing the value of the residual function and its derivative (also known as the Jacobian) with respect to $x$.
38 Once we have a way of computing the residual vector, it is now time to construct a Non-linear least squares problem using it and have Ceres solve it.
curvefitting.tex 30 %\caption{Templated functor to compute the residual for the exponential model fitting problem. Note that one instance of the functor is responsible for computing the residual for one observation.}
bundleadjustment.tex 65 examples before this is a non-trivial function and computing its
modeling.tex 6 \texttt{CostFunction} is responsible for computing
49 If \texttt{jacobians} is \texttt{NULL}, then no derivatives are returned; this is the case when computing cost only. If \texttt{jacobians[i]} is \texttt{NULL}, then the Jacobian matrix corresponding to the $i^{\textrm{th}}$ parameter block must not be returned, this is the case when the a parameter block is marked constant.
126 \texttt{MyScalarCostFunction}, \texttt{<1, 2, 2>} describe the functor as computing a
151 small changes to the appropriate parameters, and computing the slope. For
powell.tex 41 With its automatic differentiation support, Ceres allows you to define templated objects/functors that will compute the residual and it takes care of computing the Jacobians as needed and filling the \texttt{jacobians} arrays with them. For example, for $f_4(x)$ we define
solving.tex 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}.
155 computing a successful Newton step.
349 The computational cost of using a preconditioner $M$ is the cost of computing $M$ and evaluating the product $M^{-1}y$ for arbitrary vectors $y$. Thus, there are two competing factors to consider: How much of $H$'s structure is captured by $M$ so that the condition number $\kappa(HM^{-1})$ is low, and the computational cost of constructing and using $M$. The ideal preconditioner would be one for which $\kappa(M^{-1}A) =1$. $M=A$ achieves this, but it is not a practical choice, as applying this preconditioner would require solving a linear system equivalent to the unpreconditioned problem. It is usually the case that the more information $M$ has about $H$, the more expensive it is use. For example, Incomplete Cholesky factorization based preconditioners have much better convergence behavior than the Jacobi preconditioner, but are also much more expensive.
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  /external/v8/test/mjsunit/regress/
regress-1531.js 28 // Regression test for computing elements keys of arguments object. Should
  /external/guava/guava-tests/test/com/google/common/collect/
MapMakerInternalMapTest.java 1863 boolean computing = false; field in class:MapMakerInternalMapTest.DummyValueReference
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  /external/libvorbis/doc/
06-floor0.tex 52 coefficient values from the bitstream, and then computing the floor
  /external/v8/benchmarks/
base.js 30 // computing a score based on the timing measurements.
  /external/v8/src/
date.js 117 // Some of our runtime funtions for computing UTC(time) rely on
  /ndk/build/core/
build-binary.mk 363 # This is a shared library or an executable, so computing dependencies properly is
definitions-graph.mk 145 # Many graph walking operations require a work queue and computing
  /external/libffi/
ltconfig 787 # If test is not a shell built-in, we'll probably end up computing a
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  /external/antlr/antlr-3.4/runtime/ActionScript/project/src/org/antlr/runtime/
BaseRecognizer.as 356 * computing FIRST of what follows the rule reference in the
  /external/dropbear/libtommath/
bn.tex     [all...]
  /external/antlr/antlr-3.4/runtime/Delphi/Sources/Antlr3.Runtime/
Antlr.Runtime.Tree.pas 607 /// that computing parent and child index is very difficult and cumbersome.
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Antlr.Runtime.pas     [all...]
  /external/v8/test/mjsunit/
unicode-test.js     [all...]

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