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Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part II

  • Michele Berlingerio
  • Francesco Bonchi
  • Thomas Gärtner
  • Neil Hurley
  • Georgiana Ifrim
Conference proceedings ECML PKDD 2018

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11052)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 11052)

Table of contents

  1. Front Matter
    Pages I-XXX
  2. Graphs

    1. Front Matter
      Pages 1-1
    2. Ana Paula Appel, Renato L. F. Cunha, Charu C. Aggarwal, Marcela Megumi Terakado
      Pages 3-18
    3. Carl Yang, Mengxiong Liu, Frank He, Xikun Zhang, Jian Peng, Jiawei Han
      Pages 37-54
    4. Charalampos E. Tsourakakis, Shreyas Sekar, Johnson Lam, Liu Yang
      Pages 71-87
    5. Wangsu Hu, Zijun Yao, Sen Yang, Shuhong Chen, Peter J. Jin
      Pages 88-104
    6. Dhivya Eswaran, Reihaneh Rabbany, Artur W. Dubrawski, Christos Faloutsos
      Pages 105-121
    7. Aastha Nigam, Kijung Shin, Ashwin Bahulkar, Bryan Hooi, David Hachen, Boleslaw K. Szymanski et al.
      Pages 122-140
    8. Kijung Shin, Jisu Kim, Bryan Hooi, Christos Faloutsos
      Pages 141-157
    9. Mohadeseh Ganji, Jeffrey Chan, Peter J. Stuckey, James Bailey, Christopher Leckie, Kotagiri Ramamohanarao et al.
      Pages 158-174
  3. Kernel Methods

    1. Front Matter
      Pages 175-175
    2. Magda Gregorová, Jason Ramapuram, Alexandros Kalousis, Stéphane Marchand-Maillet
      Pages 177-192
    3. Valentina Zantedeschi, Rémi Emonet, Marc Sebban
      Pages 193-208
  4. Learning Paradigms

    1. Front Matter
      Pages 225-225
    2. Ondřej Kuželka, Yuyi Wang, Steven Schockaert
      Pages 259-275
    3. Andrea Zanette, Junzi Zhang, Mykel J. Kochenderfer
      Pages 276-291
    4. Majdi Khalid, Indrakshi Ray, Hamidreza Chitsaz
      Pages 292-307
  5. Matrix and Tensor Analysis

    1. Front Matter
      Pages 309-309
    2. Arto Klami, Jarkko Lagus, Joseph Sakaya
      Pages 311-326
    3. Ravdeep Pasricha, Ekta Gujral, Evangelos E. Papalexakis
      Pages 327-343
    4. Reza Babanezhad, Issam H. Laradji, Alireza Shafaei, Mark Schmidt
      Pages 344-359
    5. Urvashi Oswal, Swayambhoo Jain, Kevin S. Xu, Brian Eriksson
      Pages 360-376
  6. Online and Active Learning

    1. Front Matter
      Pages 377-377
    2. Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel
      Pages 379-395
    3. Nikos Katzouris, Evangelos Michelioudakis, Alexander Artikis, Georgios Paliouras
      Pages 396-413
    4. Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li
      Pages 414-429
    5. Tingting Zhai, Hao Wang, Frédéric Koriche, Yang Gao
      Pages 430-446
    6. Sebastian Mair, Yannick Rudolph, Vanessa Closius, Ulf Brefeld
      Pages 447-463
    7. Zhipeng Luo, Milos Hauskrecht
      Pages 464-480
  7. Pattern and Sequence Mining

    1. Front Matter
      Pages 481-481
    2. Aimene Belfodil, Adnene Belfodil, Mehdi Kaytoue
      Pages 500-516
    3. Minoru Higuchi, Kanji Matsutani, Masahito Kumano, Masahiro Kimura
      Pages 517-534
    4. Esther Galbrun, Peggy Cellier, Nikolaj Tatti, Alexandre Termier, Bruno Crémilleux
      Pages 535-551
    5. Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Phung
      Pages 569-584
    6. Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel
      Pages 585-601
  8. Probabilistic Models and Statistical Methods

    1. Front Matter
      Pages 603-603
    2. Masahiro Kohjima, Tatsushi Matsubayashi, Hiroyuki Toda
      Pages 605-620
    3. Julian Berk, Vu Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
      Pages 621-637
    4. Joan Capdevila, Jesús Cerquides, Jordi Torres, François Petitjean, Wray Buntine
      Pages 638-654
    5. Alexander Marx, Jilles Vreeken
      Pages 655-671
  9. Recommender Systems

    1. Front Matter
      Pages 673-673
    2. Zhengxiao Du, Jie Tang, Yuhui Ding
      Pages 675-690

Other volumes

  1. European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part I
  2. Machine Learning and Knowledge Discovery in Databases
    European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part II
  3. European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part III
  4. Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings

About these proceedings

Introduction

The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. 

The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. 

The contributions were organized in topical sections named as follows:
Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation.
Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. 
Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.

Keywords

artificial intelligence bayesian networks big data classification clustering data mining data security image processing learning algorithms machine learning neural networks recommender systems semantics signal filtering and prediction signal processing social networking social networks supervised learning Support Vector Machines (SVM)

Editors and affiliations

  1. 1.IBM Research - IrelandDublinIreland
  2. 2.Institute for Scientific InterchangeTurinItaly
  3. 3.University of NottinghamNottinghamUK
  4. 4.University College DublinDublinIreland
  5. 5.University College DublinDublinIreland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-10928-8
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-10927-1
  • Online ISBN 978-3-030-10928-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site