Graph-Based Representations in Pattern Recognition - Info and Reading Options

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Intro -- Preface -- Organization -- Contents -- Graph-Based Representation -- Approximation of Graph Edit Distance in Quadratic Time -- 1 Introduction -- 2 Bipartite Graph Edit Distance Approximation -- 3 Greedy Assignment Algorithms -- 3.1 Basic Greedy Assignment -- 3.2 Tie Break Strategy -- 3.3 Refined Greedy Assignment -- 3.4 Greedy Assignment Regarding Loss -- 3.5 Relations to Exact Graph Edit Distance -- 4 Experimental Evaluation -- 5 Conclusions and Future Work -- Data Graph Formulation as the Minimum-Weight Maximum-Entropy Problem -- 1 Introduction -- 2 The Minimum-Weight Maximum-Entropy Problem -- 3 The Near Homogeneous Degree Distribution (NHDD) -- 4 Optimization -- 5 Conclusions and Future Work -- An Entropic Edge Assortativity Measure -- 1 Introduction -- 2 Preliminaries -- 2.1 Entropy Contribution for Undirected Edges -- 2.2 Entropy Contribution for Directed Edges -- 3 Entropic Edge Assortativity Measure for Graphs -- 3.1 Entropic Edge Assortativity Measure for Undirected Graphs -- 3.2 Entropic Edge Assortativity Measure for Directed Graphs -- 4 Experiments and Discussion -- 4.1 Experiments and Discussion on Undirected Graphs -- 4.2 Experiments and Discussion on Directed Graphs -- 5 Conclusions -- A Subpath Kernel for Learning Hierarchical Image Representations -- 1 Introduction -- 2 Proposed Kernel -- 2.1 Adaptation to Numeric Data -- 2.2 Efficient Computation -- 2.3 Additional Improvements -- 3 Experiments -- 3.1 Experimental Setup -- 3.2 Artificial Dataset -- 3.3 Satellite Image Dataset -- Results. -- 4 Conclusion -- Coupled-Feature Hypergraph Representation for Feature Selection -- 1 Introduction -- 2 Coupled Feature Representation -- 3 Coupled Feature Hypergraph Analysis for Feature Selection -- 3.1 Hypergraph Construction via Multiple Feature Correlation -- 3.2 Computing Hyperedge Weight by Higher-Order Features Correlation

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