Similarity-Based Pattern Recognition

1. Front Matter

   Pages I-VIII

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2. A Novel Data Representation Based on Dissimilarity Increments

   • Helena Aidos, Ana Fred

   Pages 1-14

3. Characterizing Multiple Instance Datasets

   • Veronika Cheplygina, David M. J. Tax

   Pages 15-27

4. Supervised Learning of Diffusion Distance to Improve Histogram Matching

   • Tewodros M. Dagnew, Umberto Castellani

   Pages 28-37

5. Similarity Analysis from Limiting Quantum Walks

   • Manuel Curado, Francisco Escolano, Edwin R. Hancock, Farshad Nourbakhsh, Marcello Pelillo

   Pages 38-53

6. Introducing Negative Evidence in Ensemble Clustering Application in Automatic ECG Analysis

   • David G. Márquez, Ana L. N. Fred, Abraham Otero, Constantino A. García, Paulo Félix

   Pages 54-69

7. Dissimilarity Representations for Low-Resolution Face Recognition

   • Mairelys Hernández-Durán, Veronika Cheplygina, Yenisel Plasencia-Calaña

   Pages 70-83

8. Deep Metric Learning Using Triplet Network

   • Elad Hoffer, Nir Ailon

   Pages 84-92

9. Cluster Merging Based on Dominant Sets

   • Jian Hou, Chunshi Sha, Hongxia Cui, Lei Chi

   Pages 93-102

10. An Adaptive Radial Basis Function Kernel for Support Vector Data Description

    • André E. Lazzaretti, David M. J. Tax

    Pages 103-116

11. Robust Initialization for Learning Latent Dirichlet Allocation

    • Pietro Lovato, Manuele Bicego, Vittorio Murino, Alessandro Perina

    Pages 117-132

12. Unsupervised Motion Segmentation Using Metric Embedding of Features

    • Yusuf Osmanlıoğlu, Sven Dickinson, Ali Shokoufandeh

    Pages 133-145

13. Transitive Assignment Kernels for Structural Classification

    • Michele Schiavinato, Andrea Gasparetto, Andrea Torsello

    Pages 146-159

14. Large Scale Indefinite Kernel Fisher Discriminant

    • Frank-Michael Schleif, Andrej Gisbrecht, Peter Tino

    Pages 160-170

15. Similarity-Based User Identification Across Social Networks

    • Katerina Zamani, Georgios Paliouras, Dimitrios Vogiatzis

    Pages 171-185

16. Dominant-Set Clustering Using Multiple Affinity Matrices

    • Eyasu Zemene, Samuel Rota Bulò, Marcello Pelillo

    Pages 186-198

17. Discovery of Salient Low-Dimensional Dynamical Structure in Neuronal Population Activity Using Hopfield Networks

    • Felix Effenberger, Christopher Hillar

    Pages 199-208

18. Back Matter

    Pages 209-229

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This book constitutes the proceedings of the Third International Workshop on Similarity Based Pattern Analysis and Recognition, SIMBAD 2015, which was held in Copenahgen, Denmark, in October 2015. The 15 full and 8 short papers presented were carefully reviewed and selected from 30 submissions.The workshop focus on problems, techniques, applications, and perspectives: from supervisedto unsupervised learning, from generative to discriminative models, and from
theoretical issues to empirical validations.

• Pattern recognition
• machine learning theory
• machine learning approaches
• learning paradigms
• knowledge representation and reasoning
• graph representation
• kernel methods
• supervised learning
• unsupervised learning
• dissimilarity-based learning
• similarity-based learning
• non-Euclidean geometry
• algorithm analysis and problem complexity

• University of Copenhagen, Copenhagen, Denmark

  Aasa Feragen

• DAIS, Università Ca' Foscari Venezia, Venezia Mestre, Italy

  Marcello Pelillo

• Delft University of Technology, Delft, The Netherlands

  Marco Loog

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