Differentiation of matrix functionals using triangular factorization
DOI10.1090/S0025-5718-2011-02451-8zbMath1219.65044OpenAlexW2007767479MaRDI QIDQ3015047
Mark A. Lukas, Robert S. Anderssen, Frank R. de Hoog
Publication date: 8 July 2011
Published in: Mathematics of Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1090/s0025-5718-2011-02451-8
algorithmssmoothing splinesmaximum likelihoodalgorithmic differentiationtriangular factorizationcovariance selectionfirst and second derivativeslog determinantdifferentiation matrix functionalslog-det relationshipsrobust generalized cross validation
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (3)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Efficient algorithms for robust generalized cross-validation spline smoothing
- Statistical learning from a regression perspective
- Large-scale geodetic least-squares adjustment by dissection and orthogonal decomposition
- Monte Carlo estimates of the log determinant of large sparse matrices
- Matrix inversion algorithms by means of automatic differentiation
- A survey of truncated-Newton methods
- High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence
- The Elimination form of the Inverse and its Application to Linear Programming
- On computing the inverse of a sparse matrix
- Robust generalized cross-validation for choosing the regularization parameter
- The Evolution of the Minimum Degree Ordering Algorithm
- On computing certain elements of the inverse of a sparse matrix
- Numerical Linear Algebra for High-Performance Computers
- Compact Computation of the Inverse of a Matrix
- Smoothing noisy data with spline functions
This page was built for publication: Differentiation of matrix functionals using triangular factorization