Nonlinear Optimization

Extracting feasible robot parameters from dynamic coefficients using nonlinear optimization methods

We consider the problem of extracting a complete set of numerical parameters that characterize the robot dynamics, starting from the identified values of dynamic coefficients that linearly parametrize the robot dynamic equations. This information is relevant when realistic dynamic simulations have...
Preconditioning Large Indefinite Linear Systems
Solution of the trust region problem via a smooth Unconstrained Reformulation
Parallel decomposition methods for linearly constrained problems subject to simple bound with application to the SVMs training

We consider the convex quadratic linearly constrained problem with bounded variables and with huge and dense Hessian matrix that arises in many applications such as the training problem of bias support vector machines. We propose a decomposition algorithmic scheme suitable to parallel...
Novel preconditioners based on quasi–Newton updates for nonlinear conjugate gradient methods

In this paper we study new preconditioners to be used within the nonlinear conjugate gradient (NCG) method, for large scale unconstrained optimization. The rationale behind our proposal draws inspiration from quasi-Newton updates, and its aim is to possibly approximate in some sense the inverse of...
Guest Editorial - Erice 2007 Nonlinear Optimization - Special Issue of COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
Motion control of redundant robots under joint constraints: Saturation in the null space
Nonlinear Optimization: a Bridge from Theory to Applications
An unconstrained minimization method for solving low-rank SDP relaxations of the maxcut problem
AN APPROXIMATE INVERSE PRECONDITIONER IN TRUNCATED NEWTON METHODS FOR LARGE SCALE OPTIMIZATION