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  • Conference proceedings
  • © 2018

Machine Learning, Optimization, and Big Data

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

Conference proceedings info: MOD 2017.

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Table of contents (49 papers)

  1. Front Matter

    Pages I-XXI
  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. Intra-feature Random Forest Clustering

    • Michael Cohen
    Pages 41-49
  5. Dolphin Pod Optimization

    • Andrea Serani, Matteo Diez
    Pages 50-62
  6. Contraction Clustering (RASTER)

    • Gregor Ulm, Emil Gustavsson, Mats Jirstrand
    Pages 63-75
  7. On the Explicit Use of Enzyme-Substrate Reactions in Metabolic Pathway Analysis

    • Angelo Lucia, Edward Thomas, Peter A. DiMaggio
    Pages 88-99
  8. A Comparative Study on Term Weighting Schemes for Text Classification

    • Ahmad Mazyad, Fabien Teytaud, Cyril Fonlupt
    Pages 100-108
  9. Dual Convergence Estimates for a Family of Greedy Algorithms in Banach Spaces

    • S. P. Sidorov, S. V. Mironov, M. G. Pleshakov
    Pages 109-120
  10. Nonlinear Methods for Design-Space Dimensionality Reduction in Shape Optimization

    • Danny D’Agostino, Andrea Serani, Emilio F. Campana, Matteo Diez
    Pages 121-132
  11. A Differential Evolution Algorithm to Develop Strategies for the Iterated Prisoner’s Dilemma

    • Manousos Rigakis, Dimitra Trachanatzi, Magdalene Marinaki, Yannis Marinakis
    Pages 133-145
  12. 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
  13. Forecasting Natural Gas Flows in Large Networks

    • Mauro Dell’Amico, Natalia Selini Hadjidimitriou, Thorsten Koch, Milena Petkovic
    Pages 158-171
  14. A Differential Evolution Algorithm to Semivectorial Bilevel Problems

    • Maria João Alves, Carlos Henggeler Antunes
    Pages 172-185
  15. Evolving Training Sets for Improved Transfer Learning in Brain Computer Interfaces

    • Jason Adair, Alexander Brownlee, Fabio Daolio, Gabriela Ochoa
    Pages 186-197
  16. 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
  17. Multi-objective Genetic Algorithm for Interior Lighting Design

    • Alice Plebe, Mario Pavone
    Pages 222-233

Other Volumes

  1. Machine Learning, Optimization, and Big Data

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

Bibliographic Information

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access