A Generalization of the Chambolle-Pock Algorithm to Banach Spaces with Applications to Inverse Problems

For a Hilbert space setting Chambolle and Pock introduced an attractive first-order algorithm which solves a convex optimization problem and its Fenchel dual simultaneously. We present a generalization of this algorithm to Banach spaces. Moreover, under certain conditions we prove strong convergence as well as convergence rates. Due to the generalization the method becomes e ciently applicable for a wider class of problems. This fact makes it particularly interesting for solving ill-posed inverse problems on Banach spaces by Tikhonov regularization or the iteratively regularized Newton-type method, respectively.

[1]  O. Hanner On the uniform convexity ofLp andlp , 1956 .

[2]  Dennis F. Cudia The geometry of Banach spaces , 1964 .

[3]  E. Asplund,et al.  Positivity of duality mappings , 1967 .

[4]  R. Rockafellar,et al.  On the maximal monotonicity of subdifferential mappings. , 1970 .

[5]  R. Tyrrell Rockafellar,et al.  Convex Analysis , 1970, Princeton Landmarks in Mathematics and Physics.

[6]  V. Barbu,et al.  Convexity and optimization in banach spaces , 1972 .

[7]  D. Boyd The power method for lp norms , 1974 .

[8]  I. Ciorǎnescu Geometry of banach spaces, duality mappings, and nonlinear problems , 1990 .

[9]  Zongben Xu,et al.  Characteristic inequalities of uniformly convex and uniformly smooth Banach spaces , 1991 .

[10]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[11]  Ya. I. Alber Generalized Projection Operators in Banach Spaces: Properties and Applications , 1993 .

[12]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .

[13]  C. Zălinescu Convex analysis in general vector spaces , 2002 .

[14]  Wataru Takahashi,et al.  Strong Convergence of a Proximal-Type Algorithm in a Banach Space , 2002, SIAM J. Optim..

[15]  Tal Schuster,et al.  Nonlinear iterative methods for linear ill-posed problems in Banach spaces , 2006 .

[16]  David M. Paganin,et al.  Coherent X-Ray Optics , 2006 .

[17]  P. Maass,et al.  Minimization of Tikhonov Functionals in Banach Spaces , 2008 .

[18]  Heinz H. Bauschke,et al.  General Resolvents for Monotone Operators: Characterization and Extension , 2008, 0810.3905.

[19]  Marc Teboulle,et al.  A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..

[20]  Antonin Chambolle,et al.  A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging , 2011, Journal of Mathematical Imaging and Vision.

[21]  B. Hofmann,et al.  Convergence rates for the iteratively regularized Gauss–Newton method in Banach spaces , 2010 .

[22]  Antonin Chambolle,et al.  Diagonal preconditioning for first order primal-dual algorithms in convex optimization , 2011, 2011 International Conference on Computer Vision.

[23]  Patrick L. Combettes,et al.  Proximal Splitting Methods in Signal Processing , 2009, Fixed-Point Algorithms for Inverse Problems in Science and Engineering.

[24]  Stephen P. Boyd,et al.  Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..

[25]  Bingsheng He,et al.  Convergence Analysis of Primal-Dual Algorithms for a Saddle-Point Problem: From Contraction Perspective , 2012, SIAM J. Imaging Sci..

[26]  Thorsten Hohage,et al.  Convergence rates in expectation for Tikhonov-type regularization of inverse problems with Poisson data , 2012, 1204.1669.

[27]  Martin Burger,et al.  The iteratively regularized Gauss–Newton method with convex constraints and applications in 4Pi microscopy , 2011, 1106.5812.

[28]  Barbara Kaltenbacher,et al.  Regularization Methods in Banach Spaces , 2012, Radon Series on Computational and Applied Mathematics.

[29]  Tuomo Valkonen,et al.  A primal–dual hybrid gradient method for nonlinear operators with applications to MRI , 2013, 1309.5032.

[30]  G. Burton Sobolev Spaces , 2013 .

[31]  Thorsten Hohage,et al.  Iteratively regularized Newton-type methods for general data misfit functionals and applications to Poisson data , 2011, Numerische Mathematik.

[32]  Luca Baldassarre,et al.  Accelerated and Inexact Forward-Backward Algorithms , 2013, SIAM J. Optim..

[33]  Bang Công Vu,et al.  A splitting algorithm for dual monotone inclusions involving cocoercive operators , 2011, Advances in Computational Mathematics.

[34]  Dirk A. Lorenz,et al.  An accelerated forward-backward algorithm for monotone inclusions , 2014, ArXiv.

[35]  Radu Ioan Bot,et al.  On the convergence rate improvement of a primal-dual splitting algorithm for solving monotone inclusion problems , 2013, Mathematical Programming.