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  /external/ceres-solver/internal/ceres/
trust_region_minimizer.h 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
35 #include "ceres/solver.h"
51 Solver::Summary* summary);
coordinate_descent_minimizer.h 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
38 #include "ceres/solver.h"
64 Solver::Summary* summary);
70 Solver::Summary* summary);
schur_complement_solver.h 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
86 // installed. For structure from motion problems, this is solver can
92 // sparse Cholesky factorization of the Schur complement. This solver
95 // structure, it maybe better to use an iterative solver.
139 // Dense Cholesky factorization based solver.
154 // Sparse Cholesky factorization based solver.
symmetric_linear_solver_test.cc 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
33 // old Conjugate Gradients solver.
70 ConjugateGradientsSolver solver(options);
72 solver.Solve(A.get(), b.data(), per_solve_options, x.data());
127 ConjugateGradientsSolver solver(options);
129 solver.Solve(A.get(), b.data(), per_solve_options, x.data());
cgnr_solver.h 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
42 // A conjugate gradients on the normal equations solver. This directly solves
conjugate_gradients_solver.h 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
31 // Preconditioned Conjugate Gradients based solver for positive
53 // inexact Newton solver.
dense_normal_cholesky_solver.h 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
52 // equations, the solver instead solves the linear least squares
74 // library. This solver always returns a solution, it is the user's
dense_qr_solver.h 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
51 // equations, the solver instead solves the linear least squares
79 // library. This solver always returns a solution, it is the user's
block_random_access_matrix.cc 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
collections_port.cc 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
linear_operator.cc 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
matrix_proto.h 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
sparse_matrix.cc 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
  /external/clang/test/Analysis/
no-exit-cfg.c 6 // The flow-sensitive dataflow solver should work even when no block in
  /external/eigen/Eigen/
SparseCholesky 16 * Such problems can also be solved using the ConjugateGradient solver from the IterativeLinearSolvers module.
  /external/ceres-solver/
NOTICE 1 Ceres Solver - A fast non-linear least squares minimizer
3 http://code.google.com/p/ceres-solver/
  /external/eigen/bench/btl/data/
action_settings.txt 9 trisolve_vector ; "{/*1.5 triangular solver - vector (X = inv(L) X)}" ; "size" ; 4:3000
10 trisolve_matrix ; "{/*1.5 triangular solver - matrix (M = inv(L) M)}" ; "size" ; 4:3000
  /external/ceres-solver/docs/
build.tex 1 %!TEX root = ceres-solver.tex
5 \url{http://code.google.com/p/ceres-solver/}.
93 tar zxf ceres-solver-1.2.1.tar.gz
96 cmake ../ceres-solver-1.2.1
105 ../ceres-solver-1.2.1/data/problem-16-22106-pre.txt \
107 This runs Ceres for a maximum of 10 iterations using the \denseschur\ linear solver. The output should look something like this.
118 Ceres Solver Report
127 Linear solver DENSE_SCHUR DENSE_SCHUR
130 Linear Solver Threads: 1 1
179 tar zxf ceres-solver-1.2.1.tar.g
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solving.tex 1 %!TEX root = ceres-solver.tex
3 Effective use of Ceres requires some familiarity with the basic components of a nonlinear least squares solver, so before we describe how to configure the solver, we will begin by taking a brief look at how some of the core optimization algorithms in Ceres work and the various linear solvers and preconditioners that power it.
8 $ F(x) = \left[f_1(x), \hdots, f_{m}(x) \right]^{\top}$ be a $m$-dimensional function of $x$. We are interested in solving the following optimization problem~\footnote{At the level of the non-linear solver, the block and residual structure is not relevant, therefore our discussion here is in terms of an optimization problem defined over a state vector of size $n$.},
81 An inexact Newton method requires two ingredients. First, a cheap method for approximately solving systems of linear equations. Typically an iterative linear solver like the Conjugate Gradients method is used for this purpose~\cite{nocedal2000numerical}. Second, a termination rule for the iterative solver. A typical termination rule is of the form
87 Ceres supports both exact and inexact step solution strategies. When the user chooses a factorization based linear solver, the exact step Levenberg-Marquardt algorithm is used. When the user chooses an iterative linear solver, the inexact step Levenberg-Marquardt algorithm is used.
178 Setting \texttt{Solver::Options::use\_inner\_iterations} to true
184 Setting \texttt{Solver::Options::num\_threads} to the maximum numbe
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  /external/eigen/unsupported/Eigen/
Polynomials 24 * \brief This module provides a QR based polynomial solver.
39 and a QR based polynomial solver.
44 solver.
93 \section QR polynomial solver class
109 Therefore the current polynomial solver is guaranteed to provide a correct result only when the complex roots \f$r_1,r_2,...,r_d\f$ have distinct moduli i.e.
121 -# a simple use of the polynomial solver is shown;
122 -# the accuracy problem with the QR algorithm is presented: a polynomial with almost conjugate roots is provided to the solver.
  /external/ceres-solver/include/ceres/
ceres.h 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/
49 #include "ceres/solver.h"
  /external/llvm/include/llvm/CodeGen/PBQP/
HeuristicBase.h 20 /// solver behaviour implemented for a number of methods.
37 /// the solver which is using this heuristic.
72 /// \brief Construct an instance with a reference to the given solver.
73 /// @param solver The solver which is using this heuristic instance.
74 HeuristicBase(HeuristicSolverImpl<HImpl> &solver)
75 : s(solver), g(s.getGraph()) { }
77 /// \brief Get the solver which is using this heuristic instance.
78 /// @return The solver which is using this heuristic instance.
80 /// You can use this method to get access to the solver in your derive
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HeuristicSolver.h 1 //===-- HeuristicSolver.h - Heuristic PBQP Solver --------------*- C++ -*-===//
10 // Heuristic PBQP solver. This solver is able to perform optimal reductions for
26 /// \brief Heuristic PBQP solver implementation.
47 /// \brief Iterator type for edges in the solver graph.
117 /// \brief Construct a heuristic solver implementation to solve the given
122 /// \brief Get the graph being solved by this solver.
124 /// solver.
142 /// the solver graph.
145 /// in the solver graph.
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Solution.h 46 /// solver only.
53 /// solver only.
60 /// solver only.
67 /// solver only.
  /external/ceres-solver/internal/ceres/miniglog/glog/
logging.cc 1 // Ceres Solver - A fast non-linear least squares minimizer
3 // http://code.google.com/p/ceres-solver/

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