activity
20172022
most citedA unifying framework for the analysis of projection-free first-order methods under a sufficient slope condition

5 citations · 5 across the 11 of their papers we have counts for

collaborators

16 papers

math.OC2022

Retraction based Direct Search Methods for Derivative Free Riemannian Optimization

Vyacheslav Kungurtsev, Francesco Rinaldi, Damiano Zeffiro

Direct search methods represent a robust and reliable class of algorithms for solving black-box optimization problems. In this paper, we explore the application of those strategies…

math.OC2022

An oracle-based framework for robust combinatorial optimization

Enrico Bettiol, Christoph Buchheim, Marianna De Santis +1

We propose a general solution approach for min-max-robust counterparts of combinatorial optimization problems with uncertain linear objectives. We focus on the discrete scenario ca…

math.OC2021

An Improved Penalty Algorithm using Model Order Reduction for MIPDECO problems with partial observations

Dominik Garmatter, Margherita Porcelli, Francesco Rinaldi +1

This work addresses optimal control problems governed by a linear time-dependent partial differential equation (PDE) as well as integer constraints on the control. Moreover, partia…

math.OC2021

Derivative-free methods for mixed-integer nonsmooth constrained optimization

Tommaso Giovannelli, Giampaolo Liuzzi, Stefano Lucidi +1

In this paper, we consider mixed-integer nonsmooth constrained optimization problems whose objective/constraint functions are available only as the output of a black-box zeroth-ord…

math.OC2021

Frank-Wolfe and friends: a journey into projection-free first-order optimization methods

Immanuel. M. Bomze, Francesco Rinaldi, Damiano Zeffiro

Invented some 65 years ago in a seminal paper by Marguerite Straus-Frank and Philip Wolfe, the Frank-Wolfe method recently enjoys a remarkable revival, fuelled by the need of fast…

math.OC2021

A Unifying Framework for Sparsity Constrained Optimization

M. Lapucci, T. Levato, F. Rinaldi +1

In this paper, we consider the optimization problem of minimizing a continuously differentiable function subject to both convex constraints and sparsity constraints. By exploiting…