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Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part I

  • Peter A. Flach
  • Tijl De Bie
  • Nello Cristianini

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7523)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 7523)

Table of contents

  1. Front Matter
  2. Invited Talks

  3. Association Rules and Frequent Patterns

  4. Bayesian Learning and Graphical Models

    1. Maxime Gasse, Alex Aussem, Haytham Elghazel
      Pages 58-73
    2. Sebastian Tschiatschek, Peter Reinprecht, Manfred Mücke, Franz Pernkopf
      Pages 74-89
    3. Tivadar Pápai, Shalini Ghosh, Henry Kautz
      Pages 90-105
    4. Shengbo Guo, Scott Sanner, Thore Graepel, Wray Buntine
      Pages 106-121
  5. Classification

  6. Dimensionality Reduction, Feature Selection and Extraction

    1. Francis Maes, Pierre Geurts, Louis Wehenkel
      Pages 191-206
    2. Zhihong Zhang, Edwin R. Hancock, Xiao Bai
      Pages 207-222
    3. Jun Wang, Adam Woznica, Alexandros Kalousis
      Pages 223-236
    4. Zheng Zhao, James Cox, David Duling, Warren Sarle
      Pages 237-252
    5. Dimitrios Mavroeidis, Lejla Batina, Twan van Laarhoven, Elena Marchiori
      Pages 253-268
  7. Distance-Based Methods and Kernels

    1. Xianglilan Zhang, Hongnan Wang, Tony J. Collins, Zhigang Luo, Ming Li
      Pages 269-282
    2. Qiong Cao, Yiming Ying, Peng Li
      Pages 283-298
    3. Nicolas Courty, Thomas Burger, Pierre-François Marteau
      Pages 299-313
  8. Ensemble Methods

    1. Roberto D’Ambrosio, Richard Nock, Wafa Bel Haj Ali, Frank Nielsen, Michel Barlaud
      Pages 314-329
    2. Nan Li, Yang Yu, Zhi-Hua Zhou
      Pages 330-345
    3. Gilles Louppe, Pierre Geurts
      Pages 346-361
  9. Graph and Tree Mining

    1. Marion Neumann, Novi Patricia, Roman Garnett, Kristian Kersting
      Pages 378-393
    2. Fabien Diot, Elisa Fromont, Baptiste Jeudy, Emmanuel Marilly, Olivier Martinot
      Pages 394-409
    3. Li Pu, Boi Faltings
      Pages 410-425
    4. Ashraf M. Kibriya, Jan Ramon
      Pages 426-441
    5. Kathy Macropol, Ambuj Singh
      Pages 442-457
  10. Large-Scale, Distributed and Parallel Mining and Learning

    1. Thomas Seidl, Brigitte Boden, Sergej Fries
      Pages 458-473
    2. Anshumali Shrivastava, Ping Li
      Pages 474-489
    3. Khoat Than, Tu Bao Ho
      Pages 490-505
    4. M. Cissé, T. Artières, Patrick Gallinari
      Pages 506-520
    5. Evangelos E. Papalexakis, Christos Faloutsos, Nicholas D. Sidiropoulos
      Pages 521-536
    6. Qing Tao, Kang Kong, Dejun Chu, Gaowei Wu
      Pages 537-552
    7. Haoruo Peng, Zhengyu Wang, Edward Y. Chang, Shuchang Zhou, Zhihua Zhang
      Pages 553-568
  11. Multi-Relational Mining and Learning

    1. Shaohua Li, Gao Cong, Chunyan Miao
      Pages 569-584
    2. Babak Ahmadi, Kristian Kersting, Sriraam Natarajan
      Pages 585-600
    3. Xueyan Jiang, Volker Tresp, Yi Huang, Maximilian Nickel, Hans-Peter Kriegel
      Pages 601-616
    4. Houssam Nassif, Vítor Santos Costa, Elizabeth S. Burnside, David Page
      Pages 617-632
  12. Multi-Task Learning

    1. Christian Widmer, Marius Kloft, Nico Görnitz, Gunnar Rätsch
      Pages 633-647
    2. Peipei Yang, Kaizhu Huang, Cheng-Lin Liu
      Pages 648-664
    3. Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan
      Pages 665-680
    4. Jean Baptiste Faddoul, Boris Chidlovskii, Rémi Gilleron, Fabien Torre
      Pages 681-696

Other volumes

  1. Machine Learning and Knowledge Discovery in Databases
    European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part I
  2. European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II

About these proceedings

Introduction

This two-volume set LNAI 7523 and LNAI 7524 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2012, held in Bristol, UK, in September 2012. The 105 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 443 submissions. The final sections of the proceedings are devoted to Demo and Nectar papers. The Demo track includes 10 papers (from 19 submissions) and the Nectar track includes 4 papers (from 14 submissions). The papers grouped in topical sections on association rules and frequent patterns; Bayesian learning and graphical models; classification; dimensionality reduction, feature selection and extraction; distance-based methods and kernels; ensemble methods; graph and tree mining; large-scale, distributed and parallel mining and learning; multi-relational mining and learning; multi-task learning; natural language processing; online learning and data streams; privacy and security; rankings and recommendations; reinforcement learning and planning; rule mining and subgroup discovery; semi-supervised and transductive learning; sensor data; sequence and string mining; social network mining; spatial and geographical data mining; statistical methods and evaluation; time series and temporal data mining; and transfer learning.

Keywords

Bayesian network classifiers data mining hypergraphs social media tree search

Editors and affiliations

  • Peter A. Flach
    • 1
  • Tijl De Bie
    • 1
  • Nello Cristianini
    • 1
  1. 1.Intelligent Systems LaboratoryUniversity of BristolBristolUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-33460-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 2012
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-33459-7
  • Online ISBN 978-3-642-33460-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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