Machine Learning, Optimization, and Big Data

Second International Workshop, MOD 2016, Volterra, Italy, August 26-29, 2016, Revised Selected Papers

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10122)

Table of contents

  1. Front Matter
    Pages I-XVIII
  2. Eva K. Lee, Yuanbo Wang, Matthew S. Hagen, Xin Wei, Robert A. Davis, Brent M. Egan
    Pages 1-15
  3. Markus Hartikainen, Kyle Eyvindson, Kaisa Miettinen, Annika Kangas
    Pages 16-29
  4. Andrea Patané, Piero Conca, Giovanni Carapezza, Andrea Santoro, Jole Costanza, Giuseppe Nicosia
    Pages 30-44
  5. Angelo Lucia, Peter A. DiMaggio
    Pages 45-58
  6. Maxence Vandromme, Julie Jacques, Julien Taillard, Laetitia Jourdan, Clarisse Dhaenens
    Pages 70-81
  7. Leo Ghignone, Rossella Cancelliere
    Pages 82-93
  8. José A. Cordero, Antonio J. Nebro, Cristóbal Barba-González, Juan J. Durillo, José García-Nieto, Ismael Navas-Delgado et al.
    Pages 106-117
  9. Paula L. Amaral Santos, Sultan Imangaliyev, Klamer Schutte, Evgeni Levin
    Pages 118-131
  10. Agostinho Agra, Adelaide Cerveira, Cristina Requejo
    Pages 144-158
  11. Andrey Pepelyshev, Yuri Staroselskiy, Anatoly Zhigljavsky, Roman Guchenko
    Pages 159-169
  12. Andrea Bacigalupo, Giorgio Gnecco, Marco Lepidi, Luigi Gambarotta
    Pages 170-181
  13. Mauro Maria Baldi, Guido Perboli, Roberto Tadei
    Pages 182-192
  14. Diana Diaz, Tin Nguyen, Sorin Draghici
    Pages 193-203
  15. Frédéric Guillou, Romaric Gaudel, Philippe Preux
    Pages 204-215
  16. Pasqua Fabiana Lanotte, Fabio Fumarola, Donato Malerba, Michelangelo Ceci
    Pages 216-223
  17. Ivan Luciano Danesi, Cristina Rea
    Pages 224-235

About these proceedings

Introduction

This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD 2016, held in Volterra, Italy, in August 2016.
The 40 papers presented in this volume were carefully reviewed and selected from 97 submissions. These proceedings contain papers in the fields of Machine Learning, Computational Optimization and DataScience presenting a substantial array of ideas, technologies, algorithms, methods and applications.

Keywords

ant colony optimization big data data mining genetic algorithms global optimization

Editors and affiliations

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-51469-7
  • Copyright Information Springer International Publishing AG 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-51468-0
  • Online ISBN 978-3-319-51469-7
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book