mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-30 00:50:37 +08:00
Sameer Agarwal
14d8297cf9
THIS IS AN API BREAKING CHANGE. Decouple the algorithm from the sparse linear algebra library being used to perform the computation. Before this change Covariance::AlgorithmType had values DENSE_SVD EIGEN_SPARSE_QR SUITE_SPARSE_QR This has been replaced by two enums now. Covariance::Options::sparse_linear_algebra_library_type which can take values EIGEN_SPARSE, SUITE_SPARSE or CX_SPARSE. The last one is currently not supported. And Covariance::Options::algorithm_type takes values DENSE_SVD SPARSE_QR This sets the stage for future extensions of the covariance computation algorithm. Also as part of this change, the covariance computation chapter has been made a top level chapter on its own instead of being buried deep inside the Solving Non-linear Least Squares problem. Change-Id: Ibfbf60902d8d17694d9ff585047a5a57d329ab22
68 lines
2.1 KiB
ReStructuredText
68 lines
2.1 KiB
ReStructuredText
============
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Ceres Solver
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============
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Ceres Solver [#f1]_ is an open source C++ library for modeling and
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solving large, complicated optimization problems. It can be used to
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solve `Non-linear Least Squares`_ problems with bounds constraints and
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general unconstrained optimization problems. It is a mature, feature
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rich, and performant library that has been used in production at
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Google since 2010. For more, see :doc:`features`.
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`ceres-solver@googlegroups.com
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<https://groups.google.com/forum/?fromgroups#!forum/ceres-solver>`_ is
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the place for discussions and questions about Ceres Solver. We use the
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`GitHub Issue Tracker
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<https://github.com/ceres-solver/ceres-solver/issues>`_ to manage bug
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reports and feature requests.
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.. toctree::
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:maxdepth: 1
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:hidden:
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features
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installation
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tutorial
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derivatives
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nnls_modeling
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nnls_solving
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nnls_covariance
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gradient_solver
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faqs
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users
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contributing
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version_history
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bibliography
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license
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.. _Non-linear Least Squares: http://en.wikipedia.org/wiki/Non-linear_least_squares
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Cite Us
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=======
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If you use Ceres Solver for a publication, please cite it as::
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@misc{ceres-solver,
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author = "Sameer Agarwal and Keir Mierle and Others",
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title = "Ceres Solver",
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howpublished = "\url{http://ceres-solver.org}",
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}
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.. rubric:: Footnotes
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.. [#f1] While there is some debate as to who invented the method of
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Least Squares [Stigler]_, there is no questioning the fact
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that it was `Carl Friedrich Gauss
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<http://www-groups.dcs.st-and.ac.uk/~history/Biographies/Gauss.html>`_
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who brought it to the attention of the world. Using just 22
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observations of the newly discovered asteroid `Ceres
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<http://en.wikipedia.org/wiki/Ceres_(dwarf_planet)>`_, Gauss
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used the method of least squares to correctly predict when
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and where the asteroid will emerge from behind the Sun
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[TenenbaumDirector]_. We named our solver after Ceres to
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celebrate this seminal event in the history of astronomy,
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statistics and optimization.
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