There is a scientific consensus that the Mediterranean region (MedR) is warming and as the
temperature continues to rise, droughts and heat waves are becoming more frequent …

We introduce a general framework for large-scale model-based derivative-free optimization
based on iterative minimization within random subspaces. We present a probabilistic worst …

Abstract The Levenberg–Marquardt algorithm is one of the most popular algorithms for
finding the solution of nonlinear least squares problems. Across different modified variations …

In this paper we consider large scale nonlinear least-squares problems for which function
and gradient are evaluated with dynamic accuracy and propose a Levenberg–Marquardt …

We present DFO-GN, a derivative-free version of the Gauss–Newton method for solving
nonlinear least-squares problems. DFO-GN uses linear interpolation of residual values to …

In this work, a subsampled Levenberg-Marquardt algorithm is proposed for solving
nonconvex finite-sum optimization problem. At each iteration, based on subsampled function …

In this paper, we propose and analyze a finite-element method of variational data
assimilation for a second-order parabolic interface equation on a two-dimensional bounded …

In many contemporary optimization problems such as those arising in machine learning, it
can be computationally challenging or even infeasible to evaluate an entire function or its …

Much of the recent work on history matching reservoir models has focused on the iterative
Ensemble Smoother (iES) method. This is well suited for practical applications because it …

There is a scientific consensus that the Mediterranean region (MEDR) is warming and as the
temperature continues to rise, extreme events such as droughts and heat waves are …