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Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III

  • Albert Bifet
  • Michael May
  • Bianca Zadrozny
  • Ricard Gavalda
  • Dino Pedreschi
  • Francesco Bonchi
  • Jaime Cardoso
  • Myra Spiliopoulou

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9286)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 9286)

Table of contents

  1. Front Matter
    Pages I-XXX
  2. Industrial Track

    1. Front Matter
      Pages 1-1
    2. Enda Barrett, Stephen Linder
      Pages 3-19
    3. Romain Guigourès, Dominique Gay, Marc Boullé, Fabrice Clérot, Fabrice Rossi
      Pages 37-52
    4. Hani Neuvirth, Yehuda Finkelstein, Amit Hilbuch, Shai Nahum, Daniel Alon, Elad Yom-Tov
      Pages 53-67
    5. Vojtech Franc, Michal Sofka, Karel Bartos
      Pages 85-99
    6. Christian Bockermann, Kai Brügge, Jens Buss, Alexey Egorov, Katharina Morik, Wolfgang Rhode et al.
      Pages 100-115
    7. Karel Bartos, Michal Sofka
      Pages 116-132
    8. Jens Schreiter, Duy Nguyen-Tuong, Mona Eberts, Bastian Bischoff, Heiner Markert, Marc Toussaint
      Pages 133-149
    9. Helena Aidos, André Lourenço, Diana Batista, Samuel Rota Bulò, Ana Fred
      Pages 150-164
    10. Phiradet Bangcharoensap, Hayato Kobayashi, Nobuyuki Shimizu, Satoshi Yamauchi, Tsuyoshi Murata
      Pages 165-179
    11. Michal Aharon, Eshcar Hillel, Amit Kagian, Ronny Lempel, Hayim Makabee, Raz Nissim
      Pages 180-195
  3. Nectar Track

    1. Front Matter
      Pages 197-197
    2. Giorgio Corani, Alessio Benavoli, Francesca Mangili, Marco Zaffalon
      Pages 199-202
    3. Harald Bosch, Robert Krüger, Dennis Thom
      Pages 203-207
    4. Mathis Börner, Wolfgang Rhode, Tim Ruhe, for the IceCube Collaboration, Katharina Morik
      Pages 208-212
    5. Stefano Ferilli, Domenico Redavid, Floriana Esposito
      Pages 218-221
    6. Michele Berlingerio, Veli Bicer, Adi Botea, Stefano Braghin, Nuno Lopes, Riccardo Guidotti et al.
      Pages 222-226
    7. Mehdi Kaytoue, Victor Codocedo, Aleksey Buzmakov, Jaume Baixeries, Sergei O. Kuznetsov, Amedeo Napoli
      Pages 227-231
    8. Alexandros Karakasidis, Georgia Koloniari, Vassilios S. Verykios
      Pages 232-236
    9. Qian Zhang, Corrado Gioannini, Daniela Paolotti, Nicola Perra, Daniela Perrotta, Marco Quaggiotto et al.
      Pages 237-240
    10. Ricardo Vilalta, Kinjal Dhar Gupta, Ashish Mahabal
      Pages 241-244
    11. Yuxiao Dong, Nitesh V. Chawla, Jie Tang, Yang Yang, Yang Yang
      Pages 245-249
    12. Wouter Duivesteijn, Julia Thaele
      Pages 250-253
    13. Natalia Andrienko, Gennady Andrienko, Georg Fuchs, Piotr Jankowski
      Pages 254-258
    14. Yuxiao Dong, Reid A. Johnson, Nitesh V. Chawla
      Pages 259-263
  4. Demo Track

    1. Front Matter
      Pages 265-265
    2. André Lourenço, Ana Priscila Alves, Carlos Carreiras, Rui Policarpo Duarte, Ana Fred
      Pages 267-270
    3. Ilaria Tiddi, Mathieu d’Aquin, Enrico Motta
      Pages 271-275
    4. Pierre Houdyer, Albrecht Zimmerman, Mehdi Kaytoue, Marc Plantevit, Joseph Mitchell, Céline Robardet
      Pages 276-280
    5. Bijan Ranjbar-Sahraei, Julia Efremova, Hossein Rahmani, Toon Calders, Karl Tuyls, Gerhard Weiss
      Pages 281-284
    6. Andre Lamurias, Luka A. Clarke, Francisco M. Couto
      Pages 285-288
    7. Matt McVicar, Cédric Mesnage, Jefrey Lijffijt, Tijl De Bie
      Pages 289-292
    8. Ujval Kamath, Ana Costa e Silva, Michael O’Connell
      Pages 293-297
    9. Matija Piškorec, Borut Sluban, Tomislav Šmuc
      Pages 298-302
    10. Tao Jiang, Zhanhuai Li, Qun Chen, Zhong Wang, Kaiwen Li, Wei Pan
      Pages 303-307
    11. David Tolpin, Jan-Willem van de Meent, Frank Wood
      Pages 308-311
    12. Anton Dries, Angelika Kimmig, Wannes Meert, Joris Renkens, Guy Van den Broeck, Jonas Vlasselaer et al.
      Pages 312-315
    13. Natalia Andrienko, Gennady Andrienko, Georg Fuchs, Salvatore Rinzivillo, Hans-Dieter Betz
      Pages 316-319
    14. Michele Berlingerio, Stefano Braghin, Francesco Calabrese, Cody Dunne, Yiannis Gkoufas, Mauro Martino et al.
      Pages 320-324
    15. Andrey Tyukin, Stefan Kramer, Jörg Wicker
      Pages 325-328
    16. Roland Assam, Simon Feiden, Thomas Seidl
      Pages 329-332
    17. Matthijs van Leeuwen, Lara Cardinaels
      Pages 333-336
    18. Gennady Andrienko, Natalia Andrienko
      Pages 337-340
  5. Back Matter
    Pages 341-345

Other volumes

  1. European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I
  2. European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II
  3. Machine Learning and Knowledge Discovery in Databases
    European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III

About these proceedings

Introduction

The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.

Keywords

data mining foundations of machine learning and data mining knowledge discovery in databases probabilistic models and statistical methods social and graphs mining classification, regression and supervised learning clustering and unsupervised learning domain adaptation ensemble learning large scale learning and big data learning paradigms machine learning and data mining applications machine learning methodologies meta-learning nonmonotonic constraints pattern and sequence mining privacy-preserving data mining probabilistic programming recommender systems rich data mining

Editors and affiliations

  • Albert Bifet
    • 1
  • Michael May
    • 2
  • Bianca Zadrozny
    • 3
  • Ricard Gavalda
    • 4
  • Dino Pedreschi
    • 5
  • Francesco Bonchi
    • 6
  • Jaime Cardoso
    • 7
  • Myra Spiliopoulou
    • 8
  1. 1.Huawei Noah’s Ark LabShatinHong Kong
  2. 2.Siemens AG Corporate TechnologyMünchenGermany
  3. 3.IBM Research BrazilRio de JaneiroBrazil
  4. 4.Universitat Politècnica de CatalunyaBarcelonaSpain
  5. 5.Università di PisaPisaItaly
  6. 6.Eurecat / Yahoo LabsBarcelonaSpain
  7. 7.University of Porto - INESC TECPortoPortugal
  8. 8.Otto-von-Guericke UniversityMagdeburgGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-23461-8
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-23460-1
  • Online ISBN 978-3-319-23461-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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