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© 2019

Machine Learning and Knowledge Discovery in Databases

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

  • 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 11051)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 11051)

Table of contents

  1. Front Matter
    Pages I-XXXVIII
  2. Adversarial Learning

    1. Front Matter
      Pages 1-1
    2. Lucas Deecke, Robert Vandermeulen, Lukas Ruff, Stephan Mandt, Marius Kloft
      Pages 3-17
    3. Jin-Wen Wu, Fei Yin, Yan-Ming Zhang, Xu-Yao Zhang, Cheng-Lin Liu
      Pages 18-34
    4. Konstantinos Papangelou, Konstantinos Sechidis, James Weatherall, Gavin Brown
      Pages 35-51
    5. Shang-Tse Chen, Cory Cornelius, Jason Martin, Duen Horng (Polo) Chau
      Pages 52-68
  3. Anomaly and Outlier Detection

    1. Front Matter
      Pages 69-69
    2. Bryan Hooi, Dhivya Eswaran, Hyun Ah Song, Amritanshu Pandey, Marko Jereminov, Larry Pileggi et al.
      Pages 71-86
    3. Shubhranshu Shekhar, Leman Akoglu
      Pages 87-104
    4. Nikhil Gupta, Dhivya Eswaran, Neil Shah, Leman Akoglu, Christos Faloutsos
      Pages 122-138
    5. M. Y. Meghanath, Deepak Pai, Leman Akoglu
      Pages 139-156
    6. Raghavendra Chalapathy, Edward Toth, Sanjay Chawla
      Pages 173-189
  4. Applications

    1. Front Matter
      Pages 191-191
    2. Hanna Drimalla, Niels Landwehr, Irina Baskow, Behnoush Behnia, Stefan Roepke, Isabel Dziobek et al.
      Pages 193-208
    3. Silvia Makowski, Lena A. Jäger, Ahmed Abdelwahab, Niels Landwehr, Tobias Scheffer
      Pages 209-225
    4. Omid Mohamad Nezami, Mark Dras, Peter Anderson, Len Hamey
      Pages 226-240
    5. Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes
      Pages 241-256
  5. Classification

    1. Front Matter
      Pages 257-257

Other volumes

  1. DMLE 2018 and IoTStream 2018, Dublin, Ireland, September 10-14, 2018, Revised Selected Papers
  2. Machine Learning and Knowledge Discovery in Databases
    European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part I
  3. European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part II
  4. European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part III
  5. 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