46 citations · 99 across the 10 of their papers we have counts for
15 papers
Adaptivity, Anchoring, and the Exact Oracle Complexity of Stochastic Fixed-Point Iterations
Yekini Shehu
We study stochastic fixed-point iterations for nonexpansive and contractive operators on Hilbert spaces, with a single-point unbiased oracle…
Primal Methods for Constrained Variational Inequalities: Optimal Rates, Feasibility Trade-offs, and Lower Bounds
Yonghong Yao, Lateef O. Jolaoso, Yekini Shehu +1
Since Zhang et al. \cite{Zhang2025} introduced the first purely primal methods for monotone variational inequalities subject to convex functional constraints, the field has lacked…
The sharp step-size constant for one-call reflection splittings on monotone inclusions
Yekini Shehu
The forward-reflected-backward splitting of Malitsky and Tam converges weakly for step sizes , where is monotone and -Lipschitz, and the question whet…
A Parameter-Free Adaptive Reflected Gradient Method for Monotone Variational Inequalities
Yekini Shehu
We analyze a one-evaluation-per-iteration method for with monotone -Lipschitz : , , $θ…
Anderson acceleration of the proximal point method: the exact adaptive minimax, a spectral phase transition, and optimal safeguarding
Zheng Jia, Yekini Shehu, Yonghong Yao
\noindent We study residual-polynomial acceleration of the proximal point method (PPM) for maximal monotone inclusions, with Anderson acceleration (AA) as the prototypical adaptive…
Three-Operator Splitting Method with Two-Step Inertial Extrapolation
Olaniyi S. Iyiola, Lateef O. Jolaoso, Yekini Shehu
The aim of this paper is to study the weak convergence analysis of sequence of iterates generated by a three-operator splitting method of Davis and Yin incorporated with two-step i…
New Douglas-Rashford Splitting Algorithms for Generalized DC Programming with Applications in Machine Learning
Yonghong Yao, Lateef O. Jolaoso, Yekini Shehu +1
In this work, we propose some new Douglas-Rashford splitting algorithms for solving a class of generalized DC (difference of convex functions) in real Hilbert spaces. The proposed…
Linear Convergence Results for Inertial Type Projection Algorithm for Quasi-Variational Inequalities
Yonghong Yao, Lateef O. Jolaoso, Yekini Shehu
Many recently proposed gradient projection algorithms with inertial extrapolation step for solving quasi-variational inequalities in Hilbert spaces are proven to be strongly conver…
Strong Convergence of Forward-Reflected-Backward Splitting Methods for Solving Monotone Inclusions with Applications to Image Restoration and Optimal Control
Chinedu Izuchukwu, Simeon Reich, Yekini Shehu +1
In this paper, we propose and study several strongly convergent versions of the forward-reflected-backward splitting method of Malitsky and Tam for finding a zero of the sum of two…
Convergence Results of Two-Step Inertial Proximal Point Algorithm
Olaniyi S. Iyiola, Yekini Shehu
This paper proposes a two-point inertial proximal point algorithm to find zero of maximal monotone operators in Hilbert spaces. We obtain weak convergence results and non-asymptoti…
Convergence of Two Simple Methods for Solving Monotone Inclusion Problems in Reflexive Banach Spaces
Chinedu Izuchukwu, Simeon Reich, Yekini Shehu
We propose two very simple methods, the first one with constant step sizes and the second one with self-adaptive step sizes, for finding a zero of the sum of two monotone operators…
Convergence Analysis of Projection Method for Variational Inequalities
Yekini Shehu, Olaniyi. S. Iyiola, Xiao-Huan Li +1
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 i…
Convergence Results of Forward-Backward Algorithms for Sum of Monotone Operators in Banach Spaces
Yekini Shehu
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 continuo…
Weak Convergence for Variational Inequalities with Inertial-Type Method
Yekini Shehu, Olaniyi. S. Iyiola
Weak convergence of inertial iterative method for solving variational inequalities is the focus of this paper. The cost function is assumed to be non-Lipschitz and monotone. We pro…
An inertial extrapolation method for convex simple bilevel optimization
Yekini Shehu, Phan Tu Vuong, Alain Zemkoho
We consider a scalar objective minimization problem over the solution set of another optimization problem. This problem is known as simple bilevel optimization problem and has draw…