commit | 17dccef91b026e30e5eb62a35d03a419be500e25 | [log] [tgz] |
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author | Sameer Agarwal <sameeragarwal@google.com> | Tue Sep 14 08:17:21 2021 -0700 |
committer | Sameer Agarwal <sameeragarwal@google.com> | Wed Sep 15 06:21:02 2021 -0700 |
tree | f3bb526c67edb5348e2ea40584e2bb76d3cbb22d | |
parent | 03d64141ae437f7b686ca3501b744cdc4d403858 [diff] |
Add NumericDiffFirstOrderFunction This has been a long requested feature so that users can minimize functions using numeric differentiation. As part of this, I have also redone rosenbrock.cc, which now has three variants. rosenbrock.cc now uses automatic differentiation. rosenbrock_numeric_diff.cc uses numeric differentiation. rosenbrock_analytic_diff.cc uses analytic derivatives. This is analogus to how the helloworld example code is structured. The tutorial for GradientProblemSolver has also been updated to reflect this. https://github.com/ceres-solver/ceres-solver/issues/691 Change-Id: Ib0fb9e35127fe4c8299d4793bea3558722c70dd7
Ceres Solver is an open source C++ library for modeling and solving large, complicated optimization problems. It is a feature rich, mature and performant library which has been used in production at Google since 2010. Ceres Solver can solve two kinds of problems.
Please see ceres-solver.org for more information.