4 citations · 7 across the 12 of their papers we have counts for
12 papers
Complexity results and active-set identification of a derivative-free method for bound-constrained problems
Andrea Brilli, Andrea Cristofari, Giampaolo Liuzzi +1
In this paper, we analyze a derivative-free line search method designed for bound-constrained problems. Our analysis demonstrates that this method exhibits a worst-case complexity…
CMA Light: a novel Minibatch Algorithm for large-scale non convex finite sum optimization
Corrado Coppola, Giampaolo Liuzzi, Laura Palagi
The supervised training of a deep neural network on a given dataset consists in the unconstrained minimization of the finite sum of continuously differentiable functions, commonly…
Worst case complexity bounds for linesearch-type derivative-free algorithms
Andrea Brilli, Morteza Kimiaei, Giampaolo Liuzzi +1
This paper is devoted to the analysis of worst case complexity bounds for linesearch-type derivative-free algorithms for the minimization of general non-convex smooth functions. We…
A clustering heuristic to improve a derivative-free algorithm for nonsmooth optimization
Manlio Gaudioso, Giampaolo Liuzzi, Stefano Lucidi
In this paper we propose an heuristic to improve the performances of the recently proposed derivative-free method for nonsmooth optimization CS-DFN. The heuristic is based on a clu…
Convergence of ease-controlled Random Reshuffling gradient Algorithms under Lipschitz smoothness
Ruggiero Seccia, Corrado Coppola, Giampaolo Liuzzi +1
In this work, we consider minimizing the average of a very large number of smooth and possibly non-convex functions, and we focus on two widely used minibatch frameworks to tackle…
A derivative-free approach to mixed integer constrained multiobjective nonsmooth optimization
Giampaolo Liuzzi, Stefano Lucidi
In this work, we consider multiobjective optimization problems with both bound constraints on the variables and general nonlinear constraints, where objective and constraint functi…
An interior point method for nonlinear constrained derivative-free optimization
Andrea Brilli, Giampaolo Liuzzi, Stefano Lucidi
In this paper we consider constrained optimization problems where both the objective and constraint functions are of the black-box type. Furthermore, we assume that the nonlinear i…
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…
Avoiding local minima in multilayer network optimization by incremental training
Alberto De Santis, Giampaolo Liuzzi, Stefano Lucidi +1
Training a large multilayer neural network can present many difficulties due to the large number of useless stationary points. These points usually attract the minimization algorit…
An augmented Lagrangian method exploiting an active-set strategy and second-order information
Andrea Cristofari, Gianni Di Pillo, Giampaolo Liuzzi +1
In this paper, we consider nonlinear optimization problems with nonlinear equality constraints and bound constraints on the variables. For the solution of such problems, many augme…
Improving P300 Speller performance by means of optimization and machine learning
Luigi Bianchi, Chiara Liti, Giampaolo Liuzzi +2
Brain-Computer Interfaces (BCIs) are systems allowing people to interact with the environment bypassing the natural neuromuscular and hormonal outputs of the peripheral nervous sys…
Computing mixed strategies equilibria in presence of switching costs by the solution of nonconvex QP problems
Giampaolo Liuzzi, Marco Locatelli, Veronica Piccialli +1
In this paper we address game theory problems arising in the context of network security. In traditional game theory problems, given a defender and an attacker, one searches for mi…