Book Volume 7872 2013

Multiple Classifier Systems

11th International Workshop, MCS 2013, Nanjing, China, May 15-17, 2013. Proceedings

Editors:

ISBN: 978-3-642-38066-2 (Print) 978-3-642-38067-9 (Online)

Table of contents (34 chapters)

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  1. Front Matter

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    Chapter

    Pages 1-12

    Improving Simple Collaborative Filtering Models Using Ensemble Methods

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    Chapter

    Pages 13-24

    Combining Instance Information to Classify Bags

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    Chapter

    Pages 25-36

    Similarity Weighted Ensembles for Relocating Models of Rare Events

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    Chapter

    Pages 37-48

    Diversity in Classifier Ensembles: Fertile Concept or Dead End?

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    Chapter

    Pages 49-60

    Gender Classification Using Mixture of Experts from Low Resolution Facial Images

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    Chapter

    Pages 61-72

    Multi-view Multi-class Classification for Identification of Pathogenic Bacterial Strains

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    Chapter

    Pages 73-84

    Feature Level Multiple Model Fusion Using Multilinear Subspace Analysis with Incomplete Training Set and Its Application to Face Image Analysis

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    Chapter

    Pages 85-94

    Kalman Filter Based Classifier Fusion for Affective State Recognition

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    Chapter

    Pages 95-108

    Adaptive Ensemble Selection for Face Re-identification under Class Imbalance

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    Chapter

    Pages 109-120

    Self-Organizing Neural Grove and Its Application to Incremental Learning

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    Chapter

    Pages 121-133

    Cascaded Reduction and Growing of Result Sets for Combining Object Detectors

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    Chapter

    Pages 134-145

    Single Classifier Based Multiple Classifications

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    Chapter

    Pages 146-156

    Selective Ensemble of Classifier Chains

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    Chapter

    Pages 157-166

    The Link between Multiple-Instance Learning and Learning from Only Positive and Unlabelled Examples

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    Chapter

    Pages 167-178

    Stable L2-Regularized Ensemble Feature Weighting

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    Chapter

    Pages 179-189

    Selective Clustering Ensemble Based on Covariance

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    Chapter

    Pages 190-200

    Semi-supervised Clustering Ensemble for Web Video Categorization

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    Chapter

    Pages 201-211

    Coding Theory Tools for Improving Recognition Performance in ECOC Systems

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    Chapter

    Pages 212-223

    Can Diversity amongst Learners Improve Online Object Tracking?

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    Chapter

    Pages 224-235

    A New Perspective of Support Vector Clustering with Boundary Patterns

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