Skip to content
GOL

GOL

Global Optimization Laboratory "Gerardo Poggiali"

Menu

  • People
    • Paola Cappanera
    • Marianna De Santis
    • Fabio Schoen
      • Fabio Schoen personal blog
    • Fabio Tardella
    • Tommaso Aldinucci
    • Arturo Annunziata
    • Francesco Carciaghi
    • Matteo Lapucci
    • Simone Magistri
    • Pierluigi Mansueto
    • Davide Pucci
    • Marco Roma
    • Tomaso Trinci
    • Past Members and Collaborators of GOL
  • Teaching
    • Fondamenti di Ricerca Operativa (Ing Informatica) – Fundamentals of operations research (Cmputer Science Engineering)
    • Fondamenti di Ricerca Operativa (Ing Gestionale) e Ottimizzazione su Reti di Flusso
    • Optimization Methods – Metodi di Ottimizzazione
    • Modelli e Algoritmi per l’Organizzazione e la Gestione – Models and Algorithms for management and organization
  • Projects
    • AIMS (Artificial Intelligence for the Management of Shifts) project
    • Project partners
  • Theses
    • Theses: proposals
    • Theses: in progress
    • Theses: discussed
  • Resources
    • Trello
    • webgol internal wiki
    • webgol internal bibliography
  • How to reach GOL

Global Optimization methods for semi-supervised learning

A quasi-Newton based approach to train a semi-supervised Support Vector Machine.

 

Candidate: Lorenzo Norcini – graduated Feb 2017

 

image_print
Global Optimization methods for semi-supervised learning
Tagged on: Ingegneria Informatica (triennale)
Fabio Schoen February 16, 2017February 16, 2017 Theses: discussed
  • ← Machine Hearing
  • Python Global optimization for space trajectories →

Meta

  • Log in
  • Entries feed
  • Comments feed
  • WordPress.org

Recent News from the Lab

  • 2022 Summer – Two International Events Organized by GOL

  • Optimization Models

  • Master Thesis Proposals / Information Engineering & Artificial Intelligence, Management Engineering et al.

  • Open Day Engineering School

  • Introduction to Operations Research

Theses (proposals)

  • Thesis Proposals (M. Lapucci)

  • Machine Learning & Optimization for Cancer Research

  • Global Optimization methods based on Clustering, Populations, Random Projections

  • Experiments in quantum computing and optimization

  • On the combination of Clustering and Multi-Objective Approaches

COVID-19 emergency

  • Crowded Zone – a Web App for social-distancing

  • Personnel scheduling in health care

  • Covering and localization problems

  • folding@home – GPU sharing initiative to fight the virus

  • Shift planning for emergency

Copyright © 2025 GOL. Powered by WordPress. Theme: Spacious by ThemeGrill.