Multiple Classifier Systems

1. Front Matter

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2. Invited Papers

   1. Ensemble Methods for Tracking and Segmentation (Abstract)

      • Shai Avidan

      Pages 1-1

   2. Ensembles and Multiple Classifiers: A Game-Theoretic View

      • Nicolò Cesa-Bianchi

      Pages 2-5

3. Classifier Ensembles I

   1. Anomaly Detection Using Ensembles

      • Larry Shoemaker, Lawrence O. Hall

      Pages 6-15

   2. Learning to Rank with Nonlinear Monotonic Ensemble

      • Nikita Spirin, Konstantin Vorontsov

      Pages 16-25

   3. A Bayesian Approach for Combining Ensembles of GP Classifiers

      • C. De Stefano, F. Fontanella, G. Folino, A. Scotto di Freca

      Pages 26-35

4. Classifier Ensembles II

   1. Multiple Classifiers for Graph of Words Embedding

      • Jaume Gibert, Ernest Valveny, Oriol Ramos Terrades, Horst Bunke

      Pages 36-45

   2. A Dynamic Logistic Multiple Classifier System for Online Classification

      • Amber Tomas

      Pages 46-55

   3. Ensemble Methods for Reinforcement Learning with Function Approximation

      • Stefan Faußer, Friedhelm Schwenker

      Pages 56-65

5. Trees and Forests

   1. GRASP Forest: A New Ensemble Method for Trees

      • José F. Diez-Pastor, César García-Osorio, Juan J. Rodríguez, Andrés Bustillo

      Pages 66-75

   2. Ensembles of Decision Trees for Imbalanced Data

      • Juan J. Rodríguez, José F. Díez-Pastor, César García-Osorio

      Pages 76-85

   3. Compact Ensemble Trees for Imbalanced Data

      • Yubin Park, Joydeep Ghosh

      Pages 86-95

6. One-Class Classifiers

   1. Pruned Random Subspace Method for One-Class Classifiers

      • Veronika Cheplygina, David M. J. Tax

      Pages 96-105

   2. Approximate Convex Hulls Family for One-Class Classification

      • Pierluigi Casale, Oriol Pujol, Petia Radeva

      Pages 106-115

7. Multiple Kernels

   1. Generalized Augmentation of Multiple Kernels

      • Wan-Jui Lee, Robert P. W. Duin, Marco Loog

      Pages 116-125

   2. A Modified Neutral Point Method for Kernel-Based Fusion of Pattern-Recognition Modalities with Incomplete Data Sets

      • Maxim Panov, Alexander Tatarchuk, Vadim Mottl, David Windridge

      Pages 126-136

   3. Two-Stage Augmented Kernel Matrix for Object Recognition

      • Muhammad Awais, Fei Yan, Krystian Mikolajczyk, Josef Kittler

      Pages 137-146

   4. Multiple Kernel Learning via Distance Metric Learning for Interactive Image Retrieval

      • Fei Yan, Krystian Mikolajczyk, Josef Kittler

      Pages 147-156

8. Classifier Selection

   1. Dynamic Ensemble Selection for Off-Line Signature Verification

      • Luana Batista, Eric Granger, Robert Sabourin

      Pages 157-166

   2. Classifier Selection Approaches for Multi-label Problems

      • Ignazio Pillai, Giorgio Fumera, Fabio Roli

      Pages 167-176

This book constitutes the refereed proceedings of the 10th International Workshop on Multiple Classifier Systems, MCS 2011, held in Naples, Italy, in June 2011. The 36 revised papers presented together with two invited papers were carefully reviewed and selected from more than 50 submissions. The contributions are organized into sessions dealing with classifier ensembles; trees and forests; one-class classifiers; multiple kernels; classifier selection; sequential combination; ECOC; diversity; clustering; biometrics; and computer security.

• Bayesian learning
• image retrieval
• image segmentation
• kernel methods
• learning classifier systems
• motion tracking
• reinforcement learning
• algorithm analysis and problem complexity

• Department of Computer Engineering and Systems, Universitá di Napoli Federico II, Italy

  Carlo Sansone

• Centre for Vision, Speech and Signal Processing, University of Surrey, Surrey, UK

  Josef Kittler

• Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy

  Fabio Roli

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