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Sameer Agarwal3e8d1922012-11-28 17:20:22 -08001// Ceres Solver - A fast non-linear least squares minimizer
2// Copyright 2012 Google Inc. All rights reserved.
3// http://code.google.com/p/ceres-solver/
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29// Author: sameeragarwal@google.com (Sameer Agarwal)
30//
31// Limited memory positive definite approximation to the inverse
Sameer Agarwal9883fc32012-11-30 12:32:43 -080032// Hessian, using the LBFGS algorithm
33
34#ifndef CERES_INTERNAL_LOW_RANK_INVERSE_HESSIAN_H_
35#define CERES_INTERNAL_LOW_RANK_INVERSE_HESSIAN_H_
Sameer Agarwal3e8d1922012-11-28 17:20:22 -080036
37#include "ceres/internal/eigen.h"
38#include "ceres/linear_operator.h"
39
40namespace ceres {
41namespace internal {
42
Sameer Agarwal9883fc32012-11-30 12:32:43 -080043// LowRankInverseHessian is a positive definite approximation to the
44// Hessian using the limited memory variant of the
45// Broyden-Fletcher-Goldfarb-Shanno (BFGS)secant formula for
46// approximating the Hessian.
47//
48// Other update rules like the Davidon-Fletcher-Powell (DFP) are
49// possible, but the BFGS rule is considered the best performing one.
50//
51// The limited memory variant was developed by Nocedal and further
52// enhanced with scaling rule by Byrd, Nocedal and Schanbel.
53//
54// Nocedal, J. (1980). "Updating Quasi-Newton Matrices with Limited
55// Storage". Mathematics of Computation 35 (151): 773–782.
56//
57// Byrd, R. H.; Nocedal, J.; Schnabel, R. B. (1994).
58// "Representations of Quasi-Newton Matrices and their use in
59// Limited Memory Methods". Mathematical Programming 63 (4):
60class LowRankInverseHessian : public LinearOperator {
Sameer Agarwal3e8d1922012-11-28 17:20:22 -080061 public:
62 // num_parameters is the row/column size of the Hessian.
63 // max_num_corrections is the rank of the Hessian approximation.
64 // The approximation uses:
65 // 2 * max_num_corrections * num_parameters + max_num_corrections
66 // doubles.
Sameer Agarwal9883fc32012-11-30 12:32:43 -080067 LowRankInverseHessian(int num_parameters, int max_num_corrections);
68 virtual ~LowRankInverseHessian() {}
Sameer Agarwal3e8d1922012-11-28 17:20:22 -080069
Sameer Agarwal9883fc32012-11-30 12:32:43 -080070 // Update the low rank approximation. delta_x is the change in the
71 // domain of Hessian, and delta_gradient is the change in the
72 // gradient. The update copies the delta_x and delta_gradient
73 // vectors, and gets rid of the oldest delta_x and delta_gradient
74 // vectors if the number of corrections is already equal to
75 // max_num_corrections.
Sameer Agarwal3e8d1922012-11-28 17:20:22 -080076 bool Update(const Vector& delta_x, const Vector& delta_gradient);
77
78 // LinearOperator interface
79 virtual void RightMultiply(const double* x, double* y) const;
80 virtual void LeftMultiply(const double* x, double* y) const {
Sameer Agarwal509f68c2013-02-20 01:39:03 -080081 RightMultiply(x, y);
Sameer Agarwal3e8d1922012-11-28 17:20:22 -080082 }
83 virtual int num_rows() const { return num_parameters_; }
84 virtual int num_cols() const { return num_parameters_; }
85
86 private:
87 const int num_parameters_;
88 const int max_num_corrections_;
89 int num_corrections_;
90 double diagonal_;
91 Matrix delta_x_history_;
92 Matrix delta_gradient_history_;
93 Vector delta_x_dot_delta_gradient_;
94};
95
96} // namespace internal
97} // namespace ceres
Sameer Agarwal9883fc32012-11-30 12:32:43 -080098
99#endif // CERES_INTERNAL_LOW_RANK_INVERSE_HESSIAN_H_