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 …

Many problems arising from machine learning, signal & image recovery, and compressed
sensing can be casted into a monotone inclusion problem for finding a zero of the sum of …

We propose a variable metric extension of the forward–backward-forward algorithm for
finding a zero of the sum of a maximally monotone operator and a monotone Lipschitzian …

In this paper, we study a strong convergence for monotone operators. We first introduce the
hybrid type algorithm for monotone operators. Next, we obtain a strong convergence …

In this work, we introduce two modified Tseng's splitting algorithms with a new nonmonotone
adaptive step size for solving monotone inclusion problem in the framework of Banach …

Splitting methods have recently received much attention due to the fact that many nonlinear
problems arising in applied areas such as image recovery, signal processing and machine …

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 …

In this paper, we propose a novel splitting method for finding a zero point of the sum of two
monotone operators where one of them is Lipschizian. The weak convergence the method is …

We consider the primal problem of finding the zeros of the sum of a maximal monotone
operator and the composition of another maximal monotone operator with a linear …

In this paper, we discuss a proximal-descent algorithm for finding a zero of the sum of two
maximal monotone operators in a real Hilbert space. Some new properties of forward …