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Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part II

  • Michelangelo Ceci
  • Jaakko Hollmén
  • Ljupčo Todorovski
  • Celine Vens
  • Sašo Džeroski

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10535)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 10535)

Table of contents

  1. Front Matter
    Pages I-XXXIII
  2. Pattern and Sequence Mining

    1. Front Matter
      Pages 1-1
    2. Bryan Hooi, Shenghua Liu, Asim Smailagic, Christos Faloutsos
      Pages 3-19
    3. Johannes De Smedt, Galina Deeva, Jochen De Weerdt
      Pages 20-36
    4. Severin Gsponer, Barry Smyth, Georgiana Ifrim
      Pages 37-52
    5. Florian Adriaens, Jefrey Lijffijt, Tijl De Bie
      Pages 53-69
  3. Privacy and Security

    1. Front Matter
      Pages 71-71
    2. Paul Prasse, Lukáš Machlica, Tomáš Pevný, Jiří Havelka, Tobias Scheffer
      Pages 73-88
  4. Probabilistic Models and Methods

    1. Front Matter
      Pages 107-107
    2. Edwin Simpson, Steven Reece, Stephen J. Roberts
      Pages 109-125
    3. Nikolaos Tziortziotis, Christos Dimitrakakis
      Pages 126-141
    4. Fattaneh Jabbari, Joseph Ramsey, Peter Spirtes, Gregory Cooper
      Pages 142-157
    5. E. Auclair, N. Peyrard, R. Sabbadin
      Pages 158-174
    6. Mickaël Chen, Ludovic Denoyer
      Pages 175-188
    7. Anil Goyal, Emilie Morvant, Pascal Germain, Massih-Reza Amini
      Pages 205-221
    8. Michael Ciere, Carlos Gañán, Michel van Eeten
      Pages 222-237
    9. Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima
      Pages 238-250
  5. Recommendation

  6. Regression

    1. Front Matter
      Pages 303-303
    2. Martin Pavlovski, Fang Zhou, Ivan Stojkovic, Ljupco Kocarev, Zoran Obradovic
      Pages 305-321
    3. Krisztian Buza, Ladislav Peska
      Pages 322-337
    4. Katrin Ullrich, Michael Kamp, Thomas Gärtner, Martin Vogt, Stefan Wrobel
      Pages 338-354
    5. Edward Moroshko, Koby Crammer
      Pages 355-369
  7. Reinforcement Learning

    1. Front Matter
      Pages 371-371
    2. Masahiro Kohjima, Tatsushi Matsubayashi, Hiroshi Sawada
      Pages 373-388
    3. Mastane Achab, Stephan Clémençon, Aurélien Garivier, Anne Sabourin, Claire Vernade
      Pages 389-404
    4. Sylvain Lamprier, Thibault Gisselbrecht, Patrick Gallinari
      Pages 405-421
  8. Subgroup Discovery

    1. Front Matter
      Pages 423-423
    2. Antti Ukkonen, Vladimir Dzyuba, Matthijs van Leeuwen
      Pages 425-441
    3. Adnene Belfodil, Sylvie Cazalens, Philippe Lamarre, Marc Plantevit
      Pages 442-458
  9. Time Series and Streams

    1. Front Matter
      Pages 459-459
    2. Vítor Cerqueira, Luís Torgo, Fábio Pinto, Carlos Soares
      Pages 478-494
    3. Shoumik Roychoudhury, Mohamed Ghalwash, Zoran Obradovic
      Pages 495-511
    4. Bartosz Krawczyk, Przemysław Skryjomski
      Pages 512-527
    5. Romain Tavenard, Simon Malinowski, Laetitia Chapel, Adeline Bailly, Heider Sanchez, Benjamin Bustos
      Pages 528-543
    6. Magda Gregorová, Alexandros Kalousis, Stéphane Marchand-Maillet
      Pages 544-558
    7. Ammar Shaker, Waleri Heldt, Eyke Hüllermeier
      Pages 559-574
    8. Balázs Szörényi, Snir Cohen, Shie Mannor
      Pages 575-590
    9. Izaskun Oregi, Aritz Pérez, Javier Del Ser, José A. Lozano
      Pages 591-605
    10. Hyun Ah Song, Bryan Hooi, Marko Jereminov, Amritanshu Pandey, Larry Pileggi, Christos Faloutsos
      Pages 606-621
    11. Xian Wu, Yuxiao Dong, Chao Huang, Jian Xu, Dong Wang, Nitesh V. Chawla
      Pages 622-638
  10. Transfer and Multi-task Learning

    1. Front Matter
      Pages 639-639
    2. Jiyi Li, Tomohiro Arai, Yukino Baba, Hisashi Kashima, Shotaro Miwa
      Pages 657-672

Other volumes

  1. European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part I
  2. Machine Learning and Knowledge Discovery in Databases
    European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part II
  3. European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III

About these proceedings

Introduction

The three volume proceedings LNAI 10534 – 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. 

The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track. 

The contributions were organized in topical sections named as follows:
Part I: anomaly detection; computer vision; ensembles and meta learning; feature selection and extraction; kernel methods; learning and optimization, matrix and tensor factorization; networks and graphs; neural networks and deep learning.
Part II: pattern and sequence mining; privacy and security; probabilistic models and methods; recommendation; regression; reinforcement learning; subgroup discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning.
Part III: applied data science track; nectar track; and demo track.

Keywords

anomaly detection artificial intelligence Bayesian networks classification clustering algorithms data mining data security data stream image processing Kernel method learning algorithms machine learning neural networks recommender systems reinforcement learning signal processing social networking supervised learning Support Vector Machines (SVM) world wide web

Editors and affiliations

  1. 1.Università degli Studi di Bari Aldo MoroBariItaly
  2. 2.Aalto University School of ScienceEspooFinland
  3. 3.University of LjubljanaLjubljanaSlovenia
  4. 4.KU Leuven KulakKortrijkBelgium
  5. 5.Jožef Stefan InstituteLjubljanaSlovenia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-71246-8
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-71245-1
  • Online ISBN 978-3-319-71246-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site