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© 2011

Machine Learning and Data Mining in Pattern Recognition

7th International Conference, MLDM 2011, New York, NY, USA, August 30 – September 3, 2011. Proceedings

  • Petra Perner

Benefits

  • Fast-track conference proceedings

  • State-of-the-art research

  • Up-to-date results

Conference proceedings MLDM 2011

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6871)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 6871)

Table of contents

  1. Front Matter
  2. Classification and Decision Theory

    1. Nenad Tomašev, Miloš Radovanović, Dunja Mladenić, Mirjana Ivanović
      Pages 16-30
    2. Antonina Danylenko, Jonas Lundberg, Welf Löwe
      Pages 31-45
    3. Alexander Y. Liu, Cheryl E. Martin
      Pages 46-59
    4. Dhafer Lahbib, Marc Boullé, Dominique Laurent
      Pages 75-87
    5. S. Sakinah S. Ahmad, Witold Pedrycz
      Pages 99-111
    6. Shu Wu, Shengrui Wang
      Pages 112-126
    7. Houda Benbrahim
      Pages 127-139
    8. Mondelle Simeon, Robert Hilderman
      Pages 140-154
    9. Zehra Cataltepe, Abdullah Sonmez, Kadriye Baglioglu, Ayse Erzan
      Pages 155-169
    10. Tao Xu, Iker Gondra, David Chiu
      Pages 185-198
    11. Victor S. Sheng, Rahul Tada
      Pages 199-209
  3. Theory of Learning

    1. Luiz Antonio Celiberto Junior, Jackson P. Matsuura
      Pages 210-223
    2. Jamshaid G. Mohebzada, Michael M. Richter, Guenther Ruhe
      Pages 239-252

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2011, held in New York, NY, USA.

The 44 revised full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized in topical sections on classification and decision theory, theory of learning, clustering, appilication in medicine, Webmining and information mining; and machine learning and image mining.

Keywords

algorithmic learning data analysis kernel methods suppor vector machine text analysis

Editors and affiliations

  • Petra Perner
    • 1
  1. 1.Intitute of Computer Vision and Applied Computer Sciences, IBaILeipzigGermany

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