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© 2019

Machine Learning, Optimization, and Data Science

4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers

  • Giuseppe Nicosia
  • Panos Pardalos
  • Giovanni Giuffrida
  • Renato Umeton
  • Vincenzo Sciacca
Conference proceedings LOD 2018

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11331)

Also part of the Information Systems and Applications, incl. Internet/Web, and HCI book sub series (LNISA, volume 11331)

Table of contents

  1. Front Matter
    Pages I-XXII
  2. Sergio Decherchi, Andrea Cavalli
    Pages 14-25
  3. Alessio Petrozziello, Ivan Jordanov
    Pages 26-37
  4. Mateusz Pawluk, Paweł Teisseyre, Jan Mielniczuk
    Pages 51-63
  5. Sebastián Vivas, Carlos Cobos, Martha Mendoza
    Pages 64-76
  6. Ahmad Mazyad, Fabien Teytaud, Cyril Fonlupt
    Pages 92-103
  7. Jussi Hakanen, Jose Malmberg, Vesa Ojalehto, Kyle Eyvindson
    Pages 104-115
  8. Victor Gergel, Vladimir Grishagin, Ruslan Israfilov
    Pages 129-140
  9. Zekarias T. Kefato, Nasrullah Sheikh, Alberto Montresor
    Pages 141-153
  10. Danny D’Agostino, Andrea Serani, Emilio Fortunato Campana, Matteo Diez
    Pages 154-165
  11. Pierangela Bruno, Francesco Calimeri, Aldo Marzullo
    Pages 166-178
  12. Margarida Sousa, Alexandra M. Carvalho
    Pages 179-190
  13. Roy de Winter, Bas van Stein, Matthys Dijkman, Thomas Bäck
    Pages 191-203
  14. Fatimah A. Almulhim, Peter A. Thwaites, Charles C. Taylor
    Pages 204-216
  15. Stéphane Chrétien, Christophe Guyeux, Zhen-Wai Olivier Ho
    Pages 231-242

About these proceedings

Introduction

This book constitutes the post-conference proceedings of the 4th International Conference on Machine Learning, Optimization, and Data Science, LOD 2018, held in Volterra, Italy, in September 2018.
The 46 full papers presented were carefully reviewed and selected from 126 submissions. The papers cover topics in the field of machine learning, artificial intelligence,  reinforcement learning, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications.

Keywords

deep learning machine learning reinforcement learning neural networks deep reinforcement learning optimization global optimization multi-Objective optimization computational optimization data sience big data data analytics artificial intelligence

Editors and affiliations

  • Giuseppe Nicosia
    • 1
  • Panos Pardalos
    • 2
  • Giovanni Giuffrida
    • 3
  • Renato Umeton
    • 4
  • Vincenzo Sciacca
    • 5
  1. 1.University of Catania, Catania, Italy and University of ReadingReadingUK
  2. 2.University of FloridaGainesvilleUSA
  3. 3.University of CataniaCataniaItaly
  4. 4.Harvard UniversityCambridgeUSA
  5. 5.IBM, Tivoli Research LabRomeItaly

Bibliographic information

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