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Inertial proximal gradient method using adaptive stepsize for convex minimization problems. (English) Zbl 07829174

Summary: This work aims to propose an inertial proximal gradient method using the adaptive stepsize to solve unconstrained minimization problems. We prove that our algorithm weakly converges to a solution of the problems. Finally, we give numerical experiments on image restoration problem. It shows that the proposed algorithms outrun known algorithms introduced by many authors.

MSC:

65K05 Numerical mathematical programming methods
90C25 Convex programming
90C30 Nonlinear programming

References:

[1] J.Y.B. Cruz, T.T. Nghia, On the convergence of the forward-backward splitting method with linesearches, Optimization Methods and Software 31 (6) (2016) 1209-1238. · Zbl 1354.65116
[2] K. Kankam, N. Pholasa, P. Cholamjiak, On convergence and complexity of the mod-ified forwardbackward method involving new linesearches for convex minimization, Mathematical Methods in the Applied Sciences 42 (5) (2019) 1352-1362. · Zbl 1461.65162
[3] K. Kankam, P. Cholamjiak, Strong convergence of the forward-backward splitting algorithms via linesearches in Hilbert spaces, Applicable Analysis (2021) 1-20.
[4] K. Kankam, N. Pholasa, P. Cholamjiak, Hybrid forward-backward algorithms using linesearch rule for minimization problem, Thai Journal of Mathematics (2019) 17 (3) 607-625. · Zbl 07447682
[5] S. Suantai, K. Kankam, P. Cholamjiak, A novel forward-backward algorithm for solving convex minimization problem in Hilbert spaces, Mathematics (2020) 8 (1) 42.
[6] P. Cholamjiak, S. Suantai, Convergence analysis for a system of equilibrium problems and a countable family of relatively quasi-nonexpansive mappings in Banach spaces, Abstract and Applied Analysis 2010 (2010). · Zbl 1206.47069
[7] S. Suantai, W. Cholamjiak, P. Cholamjiak, An implicit iteration process for solving a fixed point problem of a finite family of multi-valued mappings in Banach spaces, Applied Mathematics Letters 25 (11) (2012) 1656-1660. · Zbl 1509.47105
[8] P. Cholamjiak, S. Suantai, A new CQ algorithm for solving split feasibility problems in Hilbert spaces, Bulletin of the Malaysian Mathematical Sciences Society 42 (5) (2019) 2517-2534. · Zbl 1529.47117
[9] A. Moudafi, M. Oliny, Convergence of a splitting inertial proximal method for mono-tone operators, Journal of Computational and Applied Mathematics 155 (2) (2003) 447-454. · Zbl 1027.65077
[10] A. Beck, M.A. Teboulle, Fast iterative shrinkage-thresholding algorithm for linear inverse problems, SIAM Journal on Imaging Sciences 2 (1) (2009) 183-202. · Zbl 1175.94009
[11] M. Verma, K.K. Shukla, A new accelerated proximal gradient technique for regular-ized multitask learning framework, Pattern Recognition Letters 95 (2017) 98-103.
[12] A. Hanjing, S. Suantai, A fast image restoration algorithm based on a fixed point and optimization method, Mathematics 8 (3) (2020) 378.
[13] D.V. Hieu, P.K. Anh, Modified forward-backward splitting method for variational inclusions, 4OR 19 (1) (2021) 127-151. · Zbl 1472.65065
[14] K.K. Tan, H.K. Xu, Approximating fixed points of non-expansive mappings by the Ishikawa iteration process, Journal of Mathematical Analysis and Applications 178 (1993) 301-301. · Zbl 0895.47048
[15] R.P. Agarwal, D.O. Regan, D.R. Sahu, Fixed Point Theory for Lipschitzian-Type Mappings with Applications, Topological Fixed Point Theory and Its Applications, Springer, New York -USA, 2009. · Zbl 1176.47037
[16] H.H. Bauschke, P.L. Combettes,Convex Analysis and Monotone Operator Theory in Hilbert Spaces, Springer, 2011. · Zbl 1218.47001
[17] Z. Opial, Weak convergence of the sequence of successive approximations for non-expansive mappings, Bulletin of the American Mathematical Society 73 (4) (1967) 591-597. · Zbl 0179.19902
[18] A.N. Iusem, B.F. Svaiter, M. Teboulle, Entropy-like proximal methods in convex programming, Mathematics of Operations Research 19 (4) (1994) 790-814. · Zbl 0821.90092
[19] Z. Wang, A.C. Bovik, H.R. Sheikh, E.P. Simoncelli, Image quality assessment: from error visibility to structural similarity, IEEE Transactions on Image Processing 13 (4) (2004) 600-612.
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