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Machine Learning and Data Mining in Pattern Recognition

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

  • Conference proceedings
  • © 2011

Overview

Editors:
  1. Petra Perner

    1. Intitute of Computer Vision and Applied Computer Sciences, IBaI, Leipzig, Germany

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

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

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Conference proceedings info: MLDM 2011.

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Table of contents (44 papers)

  1. Front Matter

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  2. Classification and Decision Theory

    1. Quadratically Constrained Maximum a Posteriori Estimation for Binary Classifier

      • Tatsuya Yokota, Yukihiko Yamashita
      Pages 1-15

    2. Hubness-Based Fuzzy Measures for High-Dimensional k-Nearest Neighbor Classification

      • Nenad Tomašev, Miloš Radovanović, Dunja Mladenić, Mirjana Ivanović
      Pages 16-30

    3. Decisions: Algebra and Implementation

      • Antonina Danylenko, Jonas Lundberg, Welf Löwe
      Pages 31-45

    4. Smoothing Multinomial Naïve Bayes in the Presence of Imbalance

      • Alexander Y. Liu, Cheryl E. Martin
      Pages 46-59

    5. ACE-Cost: Acquisition Cost Efficient Classifier by Hybrid Decision Tree with Local SVM Leaves

      • Liyun Li, Umut Topkara, Nasir Memon
      Pages 60-74

    6. Informative Variables Selection for Multi-relational Supervised Learning

      • Dhafer Lahbib, Marc Boullé, Dominique Laurent
      Pages 75-87

    7. Separability of Split Value Criterion with Weighted Separation Gains

      • Krzysztof Grąbczewski
      Pages 88-98

    8. Granular Instances Selection for Fuzzy Modeling

      • S. Sakinah S. Ahmad, Witold Pedrycz
      Pages 99-111

    9. Parameter-Free Anomaly Detection for Categorical Data

      • Shu Wu, Shengrui Wang
      Pages 112-126

    10. Fuzzy Semi-supervised Support Vector Machines

      • Houda Benbrahim
      Pages 127-139

    11. GENCCS: A Correlated Group Difference Approach to Contrast Set Mining

      • Mondelle Simeon, Robert Hilderman
      Pages 140-154

    12. Collective Classification Using Heterogeneous Classifiers

      • Zehra Cataltepe, Abdullah Sonmez, Kadriye Baglioglu, Ayse Erzan
      Pages 155-169

    13. Spherical Nearest Neighbor Classification: Application to Hyperspectral Data

      • Dalton Lunga, Okan Ersoy
      Pages 170-184

    14. Adaptive Kernel Diverse Density Estimate for Multiple Instance Learning

      • Tao Xu, Iker Gondra, David Chiu
      Pages 185-198

    15. Boosting Inspired Process for Improving AUC

      • Victor S. Sheng, Rahul Tada
      Pages 199-209

  3. Theory of Learning

    1. Investigation in Transfer Learning: Better Way to Apply Transfer Learning between Agents

      • Luiz Antonio Celiberto Junior, Jackson P. Matsuura
      Pages 210-223

    2. Exploration Strategies for Learned Probabilities in Smart Terrain

      • John Sullins
      Pages 224-238

    3. Sensitivity Analysis for Weak Constraint Generation

      • Jamshaid G. Mohebzada, Michael M. Richter, Guenther Ruhe
      Pages 239-252

    4. Dictionary Learning Based on Laplacian Score in Sparse Coding

      • Jin Xu, Hong Man
      Pages 253-264
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  1. Machine Learning and Data Mining in Pattern Recognition

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About this book

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, application in medicine, webmining and information mining; and machine learning and image mining.

Editors and Affiliations

  • Intitute of Computer Vision and Applied Computer Sciences, IBaI, Leipzig, Germany

    Petra Perner

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