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2013 | OriginalPaper | Buchkapitel

Nonsmooth Optimization Method and Sparsity

verfasst von : Kazufumi Ito

Erschienen in: Control and Optimization with PDE Constraints

Verlag: Springer Basel

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Abstract

Nonsmooth variational problems are analyzed using the Lagrange multiplier theory. In particular, the sparsity optimization method has a multitude of important applications, i.e., in imaging analysis and friction contact and inverse problems, and can be cast as nonsmooth variational problems. The optimality condition is derived and it is of the form of the complementarity systems. An effective numerical optimization method using the semismooth Newton method is then developed and analyzed. The method takes the form of primal-dual active set methods and is much more efficient than numerical optimization algorithms based on first order methods. The 0 sparsity optimization for the linear least square problem is considered. The necessary optimality condition is derived and a numerical algorithm based on the Lagrange multiplier rule to determine a solution is developed and analyzed.

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Literatur
1.
Zurück zum Zitat B. Berkels, C. Kondermann, C.S. Garbe, M. Rumpf, Reconstructing optical flow fields by motion inpainting, in Energy Minimization Methods in Computer Vision and Pattern Recognition, Lecture Notes in Computer Science, vol. 5681 (Springer, Berlin, 2009), pp. 388–400 CrossRef B. Berkels, C. Kondermann, C.S. Garbe, M. Rumpf, Reconstructing optical flow fields by motion inpainting, in Energy Minimization Methods in Computer Vision and Pattern Recognition, Lecture Notes in Computer Science, vol. 5681 (Springer, Berlin, 2009), pp. 388–400 CrossRef
2.
Zurück zum Zitat K. Bredies, D.A. Lorenz, Minimization of non-smooth, nonconvex functionals by iterative thresholding, Preprint K. Bredies, D.A. Lorenz, Minimization of non-smooth, nonconvex functionals by iterative thresholding, Preprint
3.
Zurück zum Zitat X. Chen, Z. Nashed, L. Qi, Smoothing methods and semismooth methods for nondifferentiable operator equations. SIAM J. Numer. Anal. 38, 1200–1216 (2000) MathSciNetCrossRef X. Chen, Z. Nashed, L. Qi, Smoothing methods and semismooth methods for nondifferentiable operator equations. SIAM J. Numer. Anal. 38, 1200–1216 (2000) MathSciNetCrossRef
4.
6.
Zurück zum Zitat R. Glowinski, J.L. Lions, R. Tremolieres, Numerical Analysis of Variational Inequalities (North-Holland, Amsterdam, 1981) MATH R. Glowinski, J.L. Lions, R. Tremolieres, Numerical Analysis of Variational Inequalities (North-Holland, Amsterdam, 1981) MATH
7.
Zurück zum Zitat M. Hintermüller, K. Ito, K. Kunisch, The primal-dual active set strategy as a semismooth Newton method. SIAM J. Optim. 13, 665–688 (2002) MathSciNetCrossRef M. Hintermüller, K. Ito, K. Kunisch, The primal-dual active set strategy as a semismooth Newton method. SIAM J. Optim. 13, 665–688 (2002) MathSciNetCrossRef
8.
Zurück zum Zitat S. Hüeber, G. Stadler, B. Wohlmuth, A primal-dual active set algorithm for three-dimensional contact problems with Coulomb friction. SIAM J. Sci. Comput. 30, 572–596 (2008) MathSciNetCrossRef S. Hüeber, G. Stadler, B. Wohlmuth, A primal-dual active set algorithm for three-dimensional contact problems with Coulomb friction. SIAM J. Sci. Comput. 30, 572–596 (2008) MathSciNetCrossRef
9.
Zurück zum Zitat K. Ito, B. Jin, T. Takeuchi, A regularization parameter for nonsmooth Tikhonov regularization. SIAM J. Sci. Comput. 33, 1415–1438 (2011) MathSciNetCrossRef K. Ito, B. Jin, T. Takeuchi, A regularization parameter for nonsmooth Tikhonov regularization. SIAM J. Sci. Comput. 33, 1415–1438 (2011) MathSciNetCrossRef
10.
Zurück zum Zitat K. Ito, K. Kunisch, Lagrange Multiplier Approach to Variational Problems and Applications. SIAM Advances in Design and Control (2008) CrossRef K. Ito, K. Kunisch, Lagrange Multiplier Approach to Variational Problems and Applications. SIAM Advances in Design and Control (2008) CrossRef
11.
Zurück zum Zitat K. Ito, K. Kunisch, Augmented Lagrangian methods for nonsmooth, convex optimizations in Hilbert spaces. J. Nonlinear Anal. 41, 591–616 (2000) MathSciNetCrossRef K. Ito, K. Kunisch, Augmented Lagrangian methods for nonsmooth, convex optimizations in Hilbert spaces. J. Nonlinear Anal. 41, 591–616 (2000) MathSciNetCrossRef
12.
Zurück zum Zitat K. Ito, K. Kunisch, A variational approach to sparsity optimization based on Lagrange multiplier theory, SFB-Report 2011-014, University of Graz (2011) K. Ito, K. Kunisch, A variational approach to sparsity optimization based on Lagrange multiplier theory, SFB-Report 2011-014, University of Graz (2011)
13.
Zurück zum Zitat K. Ito, K. Kunisch, Augmented Lagrangian formulation of nonsmooth, convex optimization in Hilbert spaces, in Control of Partial Differential Equations and Applications, ed. by E. Casas. Lecture Notes in Pure and Applied Mathematics, vol. 174 (1995), pp. 107–117 K. Ito, K. Kunisch, Augmented Lagrangian formulation of nonsmooth, convex optimization in Hilbert spaces, in Control of Partial Differential Equations and Applications, ed. by E. Casas. Lecture Notes in Pure and Applied Mathematics, vol. 174 (1995), pp. 107–117
14.
Zurück zum Zitat K. Ito, K. Kunisch, The primal-dual active set method for nonlinear optimal control problems with bilateral constraints. SIAM J. Control Optim. 43, 357–376 (2004) MathSciNetCrossRef K. Ito, K. Kunisch, The primal-dual active set method for nonlinear optimal control problems with bilateral constraints. SIAM J. Control Optim. 43, 357–376 (2004) MathSciNetCrossRef
15.
Zurück zum Zitat K. Kunisch, G. Stadler, Generalized Newton methods for the 2D-Signorini contact problem with friction. ESAIM Math. Model. Numer. Anal. 39, 827–854 (2005) CrossRef K. Kunisch, G. Stadler, Generalized Newton methods for the 2D-Signorini contact problem with friction. ESAIM Math. Model. Numer. Anal. 39, 827–854 (2005) CrossRef
16.
Zurück zum Zitat R.M. Leahy, B.D. Jeffs, On the design of maximally sparse beamforming array. IEEE Trans. Antennas Propag. 39, 1178–1187 (1991) CrossRef R.M. Leahy, B.D. Jeffs, On the design of maximally sparse beamforming array. IEEE Trans. Antennas Propag. 39, 1178–1187 (1991) CrossRef
17.
Zurück zum Zitat R. Mifflin, Semismooth and semiconvex functions in constrained optimization. SIAM J. Control Optim. 15, 959–972 (1977) MathSciNetCrossRef R. Mifflin, Semismooth and semiconvex functions in constrained optimization. SIAM J. Control Optim. 15, 959–972 (1977) MathSciNetCrossRef
19.
Zurück zum Zitat L. Qi, Convergence analysis of some algorithms for solving nonsmooth equations. Math. Oper. Res. 18, 227–244 (1993) MathSciNetCrossRef L. Qi, Convergence analysis of some algorithms for solving nonsmooth equations. Math. Oper. Res. 18, 227–244 (1993) MathSciNetCrossRef
20.
Zurück zum Zitat M. Ulbrich, Semismooth Newton methods for operator equations in function spaces. SIAM J. Optim. 13, 805–841 (2002) MathSciNetCrossRef M. Ulbrich, Semismooth Newton methods for operator equations in function spaces. SIAM J. Optim. 13, 805–841 (2002) MathSciNetCrossRef
21.
Zurück zum Zitat S.J. Wright, R.D. Nowak, M.A.T. Figueiredo, Sparse reconstruction by separable approximation. IEEE Trans. Signal Process. 57, 2479–2493 (2009) MathSciNetCrossRef S.J. Wright, R.D. Nowak, M.A.T. Figueiredo, Sparse reconstruction by separable approximation. IEEE Trans. Signal Process. 57, 2479–2493 (2009) MathSciNetCrossRef
22.
Zurück zum Zitat C.A. Zarzer, On Tikhonov regularization with non-convex sparsity constraints. Inverse Probl. 25, 025006 (2009) MathSciNetCrossRef C.A. Zarzer, On Tikhonov regularization with non-convex sparsity constraints. Inverse Probl. 25, 025006 (2009) MathSciNetCrossRef
Metadaten
Titel
Nonsmooth Optimization Method and Sparsity
verfasst von
Kazufumi Ito
Copyright-Jahr
2013
Verlag
Springer Basel
DOI
https://doi.org/10.1007/978-3-0348-0631-2_4