Search Results for author: Marco Locatelli

Found 6 papers, 2 papers with code

A Dynamic Programming Approach for Road Traffic Estimation

no code implementations27 Mar 2024 Mattia Laurini, Irene Saccani, Stefano Ardizzoni, Luca Consolini, Marco Locatelli

The flows of all user groups are modeled as a set of independent Poisson processes.

A Branch and Bound method for the exact parameter identification of the PK/PD model for anesthetic drugs

no code implementations25 Mar 2024 Giulia Di Credico, Luca Consolini, Mattia Laurini, Marco Locatelli, Marco Milanesi, Michele Schiavo, Antonio Visioli

We address the problem of parameter identification for the standard pharmacokinetic/pharmacodynamic (PK/PD) model for anesthetic drugs.

The Bounded Acceleration Shortest Path problem: complexity and solution algorithms

no code implementations4 Mar 2021 Stefano Ardizzoni, Luca Consolini, Mattia Laurini, Marco Locatelli

The purpose of this work is to introduce and characterize the Bounded Acceleration Shortest Path (BASP) problem, a generalization of the Shortest Path (SP) problem.

Data Structures and Algorithms Systems and Control Systems and Control 90-08

Sharp and fast bounds for the Celis-Dennis-Tapia problem

no code implementations22 Feb 2021 Luca Consolini, Marco Locatelli

In the Celis-Dennis-Tapia (CDT) problem a quadratic function is minimized over a region defined by two strictly convex quadratic constraints.

Optimization and Control

Partitioned Least Squares

2 code implementations29 Jun 2020 Roberto Esposito, Mattia Cerrato, Marco Locatelli

In this paper we propose a variant of the linear least squares model allowing practitioners to partition the input features into groups of variables that they require to contribute similarly to the final result.

Globally Optimal Registration based on Fast Branch and Bound

1 code implementation28 Jan 2019 Luca Consolini, Mattia Laurini, Marco Locatelli, Dario Lodi Rizzini

In our setting, the search domain is the set of planar rigid transformations and the objective function is the sum of the distances between each point of the transformed source set and the destination set.

Robotics

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