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Similarity-Based Pattern Recognition

Overview of attention for book
Cover of 'Similarity-Based Pattern Recognition'

Table of Contents

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    Book Overview
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    Chapter 1 Pattern Learning and Recognition on Statistical Manifolds: An Information-Geometric Review
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    Chapter 2 Dimension Reduction Methods for Image Pattern Recognition
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    Chapter 3 Efficient Regression in Metric Spaces via Approximate Lipschitz Extension
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    Chapter 4 Data Analysis of (Non-)Metric Proximities at Linear Costs
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    Chapter 5 On the Informativeness of Asymmetric Dissimilarities
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    Chapter 6 Information-Theoretic Dissimilarities for Graphs
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    Chapter 7 Information Theoretic Pairwise Clustering
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    Chapter 8 Correlation Clustering with Stochastic Labellings
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    Chapter 9 Break and Conquer: Efficient Correlation Clustering for Image Segmentation
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    Chapter 10 Multi-task Averaging via Task Clustering
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    Chapter 11 Modeling and Detecting Community Hierarchies
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    Chapter 12 Graph Characterization Using Gaussian Wave Packet Signature
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    Chapter 13 Analysis of the Schrödinger Operator in the Context of Graph Characterization
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    Chapter 14 Attributed Graph Similarity from the Quantum Jensen-Shannon Divergence
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    Chapter 15 Entropy and Heterogeneity Measures for Directed Graphs
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    Chapter 16 Fast Learning of Gamma Mixture Models with k -MLE
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    Chapter 17 Exploiting Geometry in Counting Grids
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    Chapter 18 On the Dissimilarity Representation and Prototype Selection for Signature-Based Bio-cryptographic Systems
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    Chapter 19 A Repeated Local Search Algorithm for BiClustering of Gene Expression Data
Overall attention for this book and its chapters
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Title
Similarity-Based Pattern Recognition
Published by
Springer Berlin Heidelberg, June 2013
DOI 10.1007/978-3-642-39140-8
ISBNs
978-3-64-239139-2, 978-3-64-239140-8
Editors

Hancock, Edwin, Pelillo, Marcello

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 20%
Unknown 4 80%

Demographic breakdown

Readers by professional status Count As %
Professor 2 40%
Unknown 3 60%
Readers by discipline Count As %
Computer Science 2 40%
Unknown 3 60%