TY - JOUR
AB - In this paper, we introduce a relaxed CQ method with alternated inertial step for solving split feasibility problems. We give convergence of the sequence generated by our method under some suitable assumptions. Some numerical implementations from sparse signal and image deblurring are reported to show the efficiency of our method.
AU - Shehu, Yekini
AU - Gibali, Aviv
ID - 7925
JF - Optimization Letters
SN - 1862-4472
TI - New inertial relaxed method for solving split feasibilities
ER -
TY - JOUR
AB - This paper aims to obtain a strong convergence result for a Douglas–Rachford splitting method with inertial extrapolation step for finding a zero of the sum of two set-valued maximal monotone operators without any further assumption of uniform monotonicity on any of the involved maximal monotone operators. Furthermore, our proposed method is easy to implement and the inertial factor in our proposed method is a natural choice. Our method of proof is of independent interest. Finally, some numerical implementations are given to confirm the theoretical analysis.
AU - Shehu, Yekini
AU - Dong, Qiao-Li
AU - Liu, Lu-Lu
AU - Yao, Jen-Chih
ID - 8196
JF - Optimization and Engineering
SN - 1389-4420
TI - New strong convergence method for the sum of two maximal monotone operators
ER -
TY - JOUR
AB - It is well known that many problems in image recovery, signal processing, and machine learning can be modeled as finding zeros of the sum of maximal monotone and Lipschitz continuous monotone operators. Many papers have studied forward-backward splitting methods for finding zeros of the sum of two monotone operators in Hilbert spaces. Most of the proposed splitting methods in the literature have been proposed for the sum of maximal monotone and inverse-strongly monotone operators in Hilbert spaces. In this paper, we consider splitting methods for finding zeros of the sum of maximal monotone operators and Lipschitz continuous monotone operators in Banach spaces. We obtain weak and strong convergence results for the zeros of the sum of maximal monotone and Lipschitz continuous monotone operators in Banach spaces. Many already studied problems in the literature can be considered as special cases of this paper.
AU - Shehu, Yekini
ID - 6596
IS - 4
JF - Results in Mathematics
SN - 1422-6383
TI - Convergence results of forward-backward algorithms for sum of monotone operators in Banach spaces
VL - 74
ER -
TY - CONF
AB - A Valued Constraint Satisfaction Problem (VCSP) provides a common framework that can express a wide range of discrete optimization problems. A VCSP instance is given by a finite set of variables, a finite domain of labels, and an objective function to be minimized. This function is represented as a sum of terms where each term depends on a subset of the variables. To obtain different classes of optimization problems, one can restrict all terms to come from a fixed set Γ of cost functions, called a language.
Recent breakthrough results have established a complete complexity classification of such classes with respect to language Γ: if all cost functions in Γ satisfy a certain algebraic condition then all Γ-instances can be solved in polynomial time, otherwise the problem is NP-hard. Unfortunately, testing this condition for a given language Γ is known to be NP-hard. We thus study exponential algorithms for this meta-problem. We show that the tractability condition of a finite-valued language Γ can be tested in O(3‾√3|D|⋅poly(size(Γ))) time, where D is the domain of Γ and poly(⋅) is some fixed polynomial. We also obtain a matching lower bound under the Strong Exponential Time Hypothesis (SETH). More precisely, we prove that for any constant δ<1 there is no O(3‾√3δ|D|) algorithm, assuming that SETH holds.
AU - Kolmogorov, Vladimir
ID - 6725
SN - 1868-8969
T2 - 46th International Colloquium on Automata, Languages and Programming
TI - Testing the complexity of a valued CSP language
VL - 132
ER -
TY - JOUR
AB - The main contributions of this paper are the proposition and the convergence analysis of a class of inertial projection-type algorithm for solving variational inequality problems in real Hilbert spaces where the underline operator is monotone and uniformly continuous. We carry out a unified analysis of the proposed method under very mild assumptions. In particular, weak convergence of the generated sequence is established and nonasymptotic O(1 / n) rate of convergence is established, where n denotes the iteration counter. We also present some experimental results to illustrate the profits gained by introducing the inertial extrapolation steps.
AU - Shehu, Yekini
AU - Iyiola, Olaniyi S.
AU - Li, Xiao-Huan
AU - Dong, Qiao-Li
ID - 7000
IS - 4
JF - Computational and Applied Mathematics
SN - 2238-3603
TI - Convergence analysis of projection method for variational inequalities
VL - 38
ER -