4 papers
A Unified Zeroth-Order Proximal Newton-Type Framework for Composite Optimization
Zekun Liu, Jinyan Fan
We propose a unified derivative-free proximal Newton-type algorithm framework for solving composite optimization problems formulated as the sum of a black-box function and a known…
A derivative-free Levenberg-Marquardt method for sparse nonlinear least squares problems
Yuchen Feng, Chuanlong Wang, Jinyan Fan
This paper studies sparse nonlinear least squares problems, where the Jacobian matrices are unavailable or expensive to compute, yet have some underlying sparse structures. We cons…
A derivative-free regularization algorithm for equality constrained nonlinear least squares problems
Xi Chen, Jinyan Fan
In this paper, we study the equality constrained nonlinear least squares problem, where the Jacobian matrices of the objective function and constraints are unavailable or expensive…
On the global complexity of a derivative-free Levenberg-Marquardt algorithm via orthogonal spherical smoothing
Xi Chen, Jinyan Fan
In this paper, we propose a derivative-free Levenberg-Marquardt algorithm for nonlinear least squares problems, where the Jacobian matrices are approximated via orthogonal spherica…