LNCS 10710 Giuseppe Nicosia · Panos Pardalos Giovanni Giuffrida · Renato Umeton (Eds.) Machine Learning, Optimization, and Big Data Third International Conference, MOD 2017 Volterra, Italy, September 14–17, 2017 Revised Selected Papers 123 Lecture Notes in Computer Science Commenced Publication in 1973 Founding and Former Series Editors: Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen Editorial Board David Hutchison Lancaster University, Lancaster, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M Kleinberg Cornell University, Ithaca, NY, USA Friedemann Mattern ETH Zurich, Zurich, Switzerland John C Mitchell Stanford University, Stanford, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel C Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen TU Dortmund University, Dortmund, Germany Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max Planck Institute for Informatics, Saarbrücken, Germany 10710 More information about this series at http://www.springer.com/series/7409 Giuseppe Nicosia Panos Pardalos Giovanni Giuffrida Renato Umeton (Eds.) • • Machine Learning, Optimization, and Big Data Third International Conference, MOD 2017 Volterra, Italy, September 14–17, 2017 Revised Selected Papers 123 Editors Giuseppe Nicosia University of Catania Catania Italy Giovanni Giuffrida University of Catania Catania Italy Panos Pardalos University of Florida Gainesville, FL USA Renato Umeton Harvard University Cambridge, MA USA ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-319-72925-1 ISBN 978-3-319-72926-8 (eBook) https://doi.org/10.1007/978-3-319-72926-8 Library of Congress Control Number: 2017962876 LNCS Sublibrary: SL3 – Information Systems and Applications, incl Internet/Web, and HCI © Springer International Publishing AG 2018 This work is subject to copyright All rights are reserved by the Publisher, whether the whole 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been made The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface MOD is an international conference embracing the fields of machine learning, optimization, and data science The third edition, MOD 2017, was organized during September 14–17, 2017 in Volterra (Pisa, Italy), a stunning medieval town dominating the picturesque countryside of Tuscany The key role of machine learning, reinforcement learning, artificial intelligence, large-scale optimization, and big data for developing solutions to some of the greatest challenges we are facing is undeniable MOD 2017 attracted leading experts from the academic world and industry with the aim of strengthening the connection between these institutions The 2017 edition of MOD represented a great opportunity for professors, scientists, industry experts, and postgraduate students to learn about recent developments in their own research areas and to learn about research in contiguous research areas, with the aim of creating an environment to share ideas and trigger new collaborations As chairs, it was an honor to organize a premiere conference in these areas and to have received a large variety of innovative and original scientific contributions During this edition, six plenary lectures were presented: Yi-Ke Guo, Department of Computing, Faculty of Engineering, Imperial College London, UK Founding Director of Data Science Institute Panos Pardalos, Department of Systems Engineering, University of Florida, USA Director of the Center for Applied Optimization Ruslan Salakhutdinov, Machine Learning Department, School of Computer Science at Carnegie Mellon University, USA Director of AI Research at Apple My Thai, Department of Computer and Information Science and Engineering, University of Florida, USA Jun Pei, Hefei University of Technology, China Vincenzo Sciacca, Cloud and Cognitive Division – IBM Rome, Italy There were also two tutorial speakers: Domenico Talia, Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica Università della Calabria, Italy Xin–She Yang, School of Science and Technology – Middlesex University London, UK Moreover, the conference hosted the second edition of the industrial session on “Machine Learning, Optimization and Data Science for Real-World Applications”: Luca Maria Aiello, Nokia Bell Labs, UK Pierpaolo Basile, University of Bari, Italy VI Preface Carlos Castillo, Universitat Pompeu Fabra in Barcelona, Spain Moderator: Aris Anagnostopoulos, Sapienza University of Rome, Italy We received 126 submissions from 46 countries and five continents; each manuscript was independently reviewed by a committee formed by at least five members through a blind review process These proceedings contain 49 research articles written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications For MOD 2017, Springer generously sponsored the MOD Best Paper Award This year, the paper by Khaled Sayed, Cheryl Telmer, Adam Butchy, and Natasa Miskov-Zivanov titled “Recipes for Translating Big Data Machine Reading to Executable Cellular Signaling Models” received the MOD Best Paper Award This conference could not have been organized without the contributions of these researchers, and so we thank them all for participating A sincere thank you also goes to all the Program Committee, formed by more than 300 scientists from academia and industry, for their valuable work of selecting the scientific contributions Finally, we would like to express our appreciation to the keynote speakers, tutorial speakers, and the industrial panel who accepted our invitation, and to all the authors who submitted their research papers to MOD 2017 September 2017 Giuseppe Nicosia Panos Pardalos Giovanni Giuffrida Renato Umeton Organization General Chair Renato Umeton Harvard University, USA Conference and Technical Program Committee Co-chairs Giuseppe Nicosia Panos Pardalos Giovanni Giuffrida University of Catania, Italy and University of Reading, UK University of Florida, USA University of Catania, Italy Tutorial Chair Giuseppe Narzisi New York University Tandon School of Engineering, USA Industrial Session Chairs Ilaria Bordino Marco Firrincieli Fabio Fumarola Francesco Gullo UniCredit UniCredit UniCredit UniCredit R&D, R&D, R&D, R&D, Italy Italy Italy Italy Organizing Committee Piero Conca Jole Costanza Giorgio Jansen Giuseppe Narzisi Andrea Patane’ Andrea Santoro Renato Umeton CNR, Italy Italian Institute of Technology, Milan, Italy University of Catania, Italy New York University Tandon School of Engineering, USA University of Oxford, UK Queen Mary University London, UK Harvard University, USA Technical Program Committee Agostinho Agra Kerem Akartunali Richard Allmendinger Aris Anagnostopoulos Davide Anguita Universidade de Aveiro, Portugal University of Strathclyde, UK The University of Manchester, UK Università di Roma La Sapienza, Italy University of Genoa, Italy VIII Organization Takaya Arita Jason Atkin Chloe-Agathe Azencott Jaume Bacardit James Bailey Baski Balasundaram Elena Baralis Xabier E Barandiaran Cristobal Barba-Gonzalez Helio J C Barbosa Roberto Battiti Lucia Beccai Aurelien Bellet Gerardo Beni Khaled Benkrid Peter Bentley Katie Bentley Heder Bernardino Daniel Berrar Adam Berry Luc Berthouze Martin Berzins Mauro Birattari Leonidas Bleris Christian Blum Paul Bourgine Anthony Brabazon Paulo Branco Juergen Branke Larry Bull Tadeusz Burczynski Robert Busa-Fekete Sergiy I Butenko Stefano Cagnoni Yizhi Cai Guido Caldarelli Alexandre Campo Angelo Cangelosi Salvador Eugenio Caoili Timoteo Carletti Jonathan Carlson Celso Carneiro Ribeiro Michelangelo Ceci Adelaide Cerveira Uday Chakraborty Nagoya University, Japan The University of Nottingham, UK Institut Curie Research Centre, Paris, France Newcastle University, UK University of Melbourne, Australia Oklahoma State University, USA Politecnico di Torino, Italy University of the Basque Country, Spain University of Malaga, Spain Laboratório Nacional de Computacao Cientifica, Brazil University of Trento, Italy Istituto Italiano di Tecnologia, Italy Inria Lille, France University of California at Riverside, USA The University of Edinburgh, UK University College London, UK Harvard Medical School, USA Universidade Federal de Juiz de Fora, Brazil Tokyo Institute of Technology, Japan CSIRO, Australia University of Sussex, UK SCI Institute, University of Utah, USA IRIDIA, Université Libre de Bruxelles, Belgium University of Texas at Dallas, USA Spanish National Research Council, Spain École Polytechnique Paris, France University College Dublin, Ireland Instituto Superior Tecnico, Portugal University of Warwick, UK University of the West of England, UK Polish Academy of Sciences, Poland Yahoo! Research, NY, USA Texas A&M University, USA University of Parma, Italy University of Edinburgh, UK IMT Lucca, Italy Université Libre de Bruxelles, Belgium University of Plymouth, UK University of the Philippines Manila, Philippines University of Namur, Belgium Microsoft Research, USA Universidade Federal Fluminense, Brazil University of Bari, Italy Universidade de Tras-os-Montes e Alto Douro, Portugal University of Missouri – St Louis, USA Organization Xu Chang W Art Chaovalitwongse Antonio Chella Ying-Ping Chen Haifeng Chen Keke Chen Gregory Chirikjian Silvia Chiusano Miroslav Chlebik Sung-Bae Cho Yonsei Anders Christensen Dominique Chu Philippe Codognet Carlos Coello Coello George Coghill Pietro Colombo David Cornforth Luís Correia Chiara Damiani Thomas Dandekar Ivan Luciano Danesi Christian Darabos Kalyanmoy Deb Nicoletta Del Buono Jordi Delgado Ralf Der Clarisse Dhaenens Barbara Di Camillo Gianni Di Caro Luigi Di Caro Luca Di Gaspero Peter Dittrich Federico Divina Stephan Doerfel Devdatt Dubhashi George Dulikravich Juan J Durillo Omer Dushek Marc Ebner Pascale Ehrenfreund Gusz Eiben Aniko Ekart Talbi El-Ghazali Michael Elberfeld Michael T M Emmerich Andries Engelbrecht IX University of Sydney, Australia University of Washington, USA Università di Palermo, Italy National Chiao Tung University, Taiwan NEC Labs, USA Wright State University, USA Johns Hopkins University, USA Politecnico di Torino, Italy University of Sussex, UK University, South Korea Lisbon University Institute, Portugal University of Kent, UK University Pierre and Marie Curie – Paris 6, France CINVESTAV-IPN, Mexico University of Aberdeen, UK University of Insubria, Italy University of Newcastle, UK University of Lisbon, Portugal University of Milan-Bicocca, Italy University of Würzburg, Germany Unicredit Bank, Italy Dartmouth College, USA Michigan State University, USA University of Bari, Italy Universitat Politecnica de Catalunya, Spain MPG, Germany Université Lille, France University of Padua, Italy IDSIA, Switzerland University of Turin, Italy University of Udine, Italy Friedrich Schiller University of Jena, Germany Pablo de Olavide University of Seville, Spain Kassel University, Germany Chalmers University, Sweden Florida International University, USA University of Innsbruck, Austria University of Oxford, UK Ernst-Moritz-Arndt-Universität Greifswald, Germany The George Washington University, USA VU Amsterdam, The Netherlands Aston University, UK University of Lille, France RWTH Aachen University, Germany Leiden University, The Netherlands University of Pretoria, South Africa ... − Cinf −up , γ) and Cinf −up = rand( , C) (7) 2 γsup−down − γ Csup−down − C , γ) and Csup−down = rand( , C) γsup−down = rand( 2 (8) γsup−up = rand(γsup−up ∗ 10) and Csup−up = rand(Csup−up ∗ 10)... of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and. .. picturesque countryside of Tuscany The key role of machine learning, reinforcement learning, artificial intelligence, large-scale optimization, and big data for developing solutions to some of the greatest