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Machine Learning, Optimization, and Big Data

Third International Conference, MOD 2017, Volterra, Italy, September 14–17, 2017, Revised Selected Papers

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Giuseppe Nicosia

    1. University of Catania, Catania, Italy

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  2. Panos Pardalos

    1. University of Florida, Gainesville, USA

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  3. Giovanni Giuffrida

    1. University of Catania, Catania, Italy

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  4. Renato Umeton

    1. Harvard University, Cambridge, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10710)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: MOD 2017.

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Table of contents (49 papers)

  1. Front Matter

    Pages I-XXI
    Download chapter PDF

  2. Recipes for Translating Big Data Machine Reading to Executable Cellular Signaling Models

    • Khaled Sayed, Cheryl A. Telmer, Adam A. Butchy, Natasa Miskov-Zivanov
    Pages 1-15

  3. Improving Support Vector Machines Performance Using Local Search

    • S. Consoli, J. Kustra, P. Vos, M. Hendriks, D. Mavroeidis
    Pages 16-28

  4. Projective Approximation Based Quasi-Newton Methods

    • Alexander Senov
    Pages 29-40

  5. Intra-feature Random Forest Clustering

    • Michael Cohen
    Pages 41-49

  6. Dolphin Pod Optimization

    • Andrea Serani, Matteo Diez
    Pages 50-62

  7. Contraction Clustering (RASTER)

    • Gregor Ulm, Emil Gustavsson, Mats Jirstrand
    Pages 63-75

  8. Deep Statistical Comparison Applied on Quality Indicators to Compare Multi-objective Stochastic Optimization Algorithms

    • Tome Eftimov, Peter Korošec, Barbara Koroušić Seljak
    Pages 76-87

  9. On the Explicit Use of Enzyme-Substrate Reactions in Metabolic Pathway Analysis

    • Angelo Lucia, Edward Thomas, Peter A. DiMaggio
    Pages 88-99

  10. A Comparative Study on Term Weighting Schemes for Text Classification

    • Ahmad Mazyad, Fabien Teytaud, Cyril Fonlupt
    Pages 100-108

  11. Dual Convergence Estimates for a Family of Greedy Algorithms in Banach Spaces

    • S. P. Sidorov, S. V. Mironov, M. G. Pleshakov
    Pages 109-120

  12. Nonlinear Methods for Design-Space Dimensionality Reduction in Shape Optimization

    • Danny D’Agostino, Andrea Serani, Emilio F. Campana, Matteo Diez
    Pages 121-132

  13. A Differential Evolution Algorithm to Develop Strategies for the Iterated Prisoner’s Dilemma

    • Manousos Rigakis, Dimitra Trachanatzi, Magdalene Marinaki, Yannis Marinakis
    Pages 133-145

  14. Automatic Creation of a Large and Polished Training Set for Sentiment Analysis on Twitter

    • Stefano Cagnoni, Paolo Fornacciari, Juxhino Kavaja, Monica Mordonini, Agostino Poggi, Alex Solimeo et al.
    Pages 146-157

  15. Forecasting Natural Gas Flows in Large Networks

    • Mauro Dell’Amico, Natalia Selini Hadjidimitriou, Thorsten Koch, Milena Petkovic
    Pages 158-171

  16. A Differential Evolution Algorithm to Semivectorial Bilevel Problems

    • Maria João Alves, Carlos Henggeler Antunes
    Pages 172-185

  17. Evolving Training Sets for Improved Transfer Learning in Brain Computer Interfaces

    • Jason Adair, Alexander Brownlee, Fabio Daolio, Gabriela Ochoa
    Pages 186-197

  18. Hybrid Global/Local Derivative-Free Multi-objective Optimization via Deterministic Particle Swarm with Local Linesearch

    • Riccardo Pellegrini, Andrea Serani, Giampaolo Liuzzi, Francesco Rinaldi, Stefano Lucidi, Emilio F. Campana et al.
    Pages 198-209

  19. Artificial Bee Colony Optimization to Reallocate Personnel to Tasks Improving Workplace Safety

    • Beatrice Lazzerini, Francesco Pistolesi
    Pages 210-221

  20. Multi-objective Genetic Algorithm for Interior Lighting Design

    • Alice Plebe, Mario Pavone
    Pages 222-233
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  1. Machine Learning, Optimization, and Big Data

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About this book

This book constitutes the post-conference proceedings of the Third International Workshop on Machine Learning, Optimization, and Big Data, MOD 2017, held in Volterra, Italy, in September 2017.

The 50 full papers presented were carefully reviewed and selected from 126 submissions. The papers cover topics in the field of machine learning, artificial intelligence, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications.


Editors and Affiliations

  • University of Catania, Catania, Italy

    Giuseppe Nicosia, Giovanni Giuffrida

  • University of Florida, Gainesville, USA

    Panos Pardalos

  • Harvard University, Cambridge, USA

    Renato Umeton

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