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Graph Kernels

Among the data structures commonly used in machine learning, graphs are arguably one of the most general. Graphs allow the modelling;

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Bridging The Gap Between Graph Edit Distance And Kernel Machines

In graph-based structural pattern recognition, the idea is to transform patterns into graphs and perform the analysis and recognition;

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Graph-Based Representations in Pattern Recognition

This book constitutes the refereed proceedings of the 9th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern;

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Creativity in Load-Balance Schemes for Multi/Many-Core Heterogeneous Graph Computing

-balance schemes for heterogeneous graph processing, and trends and challenges in large-scale HPC network analysis''--;

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Regularization, Optimization, Kernels, and Support Vector Machines

multi-layer SVMs Explores nonparametric feature selection, basis pursuit methods, and robust compressive sensing Describes graph-based;

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Regularization, Optimization, Kernels, and Support Vector Machines

graph-based regularization methods for single- and multi-task learning Considers regularized methods for dictionary learning and;

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Random Walks and Heat Kernels on Graphs

This introduction to random walks on infinite graphs gives particular emphasis to graphs with polynomial volume growth. It offers an;

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Treewidth, Kernels, and Algorithms

included in this volume show the many transformative discoveries made by H.L. Bodlaender in the areas of graph algorithms, parameterized complexity;

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Theory of Reproducing Kernels and Applications

This book provides a large extension of the general theory of reproducing kernels published by N. Ar;...

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Heat Kernels And Spectral Theory

An advanced monograph on a central topic in the theory of differential equations, Heat Kernels and S;...

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Theory of Agglomerative Hierarchical Clustering

method for a greater number of objects. A fundamental theorem for single linkage using a fuzzy graph is proved, which uncovers several;

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Generalized Mercer Kernels and Reproducing Kernel Banach Spaces

This article studies constructions of reproducing kernel Banach spaces (RKBSs) which may be viewed a;...

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Kernels For Structured Data

-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph;

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Kernel Methods and Estimation of Extreme Value Index

This book is a blend of rigorous probability theories and interesting statistical methodologies. It ;...

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Cambridge Tracts in Mathematics

This tract is devoted to the theory of linear equations, mainly of the second kind, associated with ;...

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Graph Polynomials

This book covers both theoretical and practical results for graph polynomials. Graph polynomials have been developed for measuring;

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Graph Polynomials

This book covers both theoretical and practical results for graph polynomials. Graph polynomials have been developed for measuring;

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Graph-Based Representations in Pattern Recognition

This book constitutes the refereed proceedings of the 12th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern;

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Human Interaction with Graphs

Interacting with graphs using queries has emerged as an important research problem for real-world applications that center on large graph;

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The Practitioner's Guide to Graph Data Applying Graph Thinking and Graph Technologies to Solve Complex Problems

Graph data closes the gap between the way humans and computers view the world. While computers rely on static rows and columns of data;

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Chromatic Graph Theory

Beginning with the origin of the four color problem in 1852, the field of graph colorings has developed into one of the most popular areas;

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Graph-Based Representations in Pattern Recognition

This book constitutes the refereed proceedings of the 10th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern;

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Knowledge Graph and Semantic Computing: Knowledge Graph Empowers New Infrastructure Construction

This book constitutes the refereed proceedings of the 6th China Conference on Knowledge Graph and Semantic Computing, CCKS 2021, held;

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Graph Data Mining

Graph data is powerful, thanks to its ability to model arbitrary relationship between objects and is encountered in a range of real-world;

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Graph Databases in Action

Graph Databases in Action teaches readers everything they need to know to begin building and running applications powered by graph;

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Reducibility of Graphs and Digraphs

Reducibility of Graphs is one of the importent subject in the restrection problem in Graph Theory.In fact the deletion of vertices(edges;

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Querying Graphs

Graph data modeling and querying arises in many practical application domains such as social and biological networks where the primary;

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