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Similarity-Based Pattern Analysis and Recognition

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Table of Contents

Introduction: The SIMBAD Project Marcello Pelillo Part I: Foundational Issues Non-Euclidean Dissimilarities: Causes, Embedding and Informativeness Robert P. W. Duin, Elzbieta Pekalska, and Marco Loog SIMBAD: Emergence of Pattern Similarity Joachim M. Buhmann Part II: Deriving Similarities for Non-vectorial Data On the Combination of Information Theoretic Kernels with Generative Embeddings Pedro M. Q. Aguiar, Manuele Bicego, Umberto Castellani, Mario A. T. Figueiredo, Andre T. Martins, Vittorio Murino, Alessandro Perina, and Aydin Ulas Learning Similarities from Examples under the Evidence Accumulation Clustering Paradigm Ana L. N. Fred, Andre Lourenco, Helena Aidos, Samuel Rota Bulo, Nicola Rebagliati, Mario Figueiredo, and Marcello Pelillo Part III: Embedding and Beyond Geometricity and Embedding Peng Ren, Furqan Aziz, Lin Han, Eliza Xu, Richard C. Wilson, and Edwin R. Hancock Structure Preserving Embedding of Dissimilarity Data Volker Roth, Thomas J. Fuchs, Julia E. Vogt, Sandhya Prabhakaran, and Joachim M. Buhmann A Game-Theoretic Approach to Pairwise Clustering and Matching Marcello Pelillo, Samuel Rota Bulo, Andrea Torsello, Andrea Albarelli, and Emanuele Rodola Part IV: Applications Automated Analysis of Tissue Micro-Array Images on the Example of Renal Cell Carcinoma Peter J. Schuffler, Thomas J. Fuchs, Cheng Soon Ong, Volker Roth, and Joachim M. Buhmann Analysis of Brain Magnetic Resonance (MR) Scans for the Diagnosis of Mental Illness Aydin Ulas, Umberto Castellani, Manuele Bicego, Vittorio Murino, Marcella Bellani, Michele Tansella, and Paolo Brambilla

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