3 citations · 7 across the 5 of their papers we have counts for
5 papers
A derivative-free trust-region approach for Low Order-Value Optimization problems
Anderson E. Schwertner, Francisco N. C. Sobral
The Low Order-Value Optimization (LOVO) problem involves minimizing the minimum among a finite number of function values within a feasible set. LOVO has several practical applicati…
Polynomial worst-case iteration complexity of quasi-Newton primal-dual interior point algorithms for linear programming
Jacek Gondzio, Francisco N. C. Sobral
Quasi-Newton methods are well known techniques for large-scale numerical optimization. They use an approximation of the Hessian in optimization problems or the Jacobian in system o…
On complexity constants of linear and quadratic models for derivative-free trust-region algorithms
A. E. Schwertner, F. N. C. Sobral
Complexity analysis has become an important tool in the convergence analysis of optimization algorithms. For derivative-free optimization algorithms, it is not different. Interesti…
A robust method based on LOVO functions for solving least squares problems
E. V. Castelani, R. Lopes, W. V. I. Shirabayashi +1
The robust adjustment of nonlinear models to data is considered in this paper. When data comes from real experiments, it is possible that measurement errors cause the appearance of…
Quasi-Newton approaches to Interior Point Methods for quadratic problems
J. Gondzio, F. N. C. Sobral
Interior Point Methods (IPM) rely on the Newton method for solving systems of nonlinear equations. Solving the linear systems which arise from this approach is the most computation…