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Deterministic Walk on Random Graph Data Fusion and Emergence of Patterns

, communication and post-processing opportunities.As they are distributed in nature and works based on local information and local control algorithms they;

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Graph Searching Games and Probabilistic Methods

Graph Searching Games and Probabilistic Methods is the first book that focuses on the intersection of graph searching games and;

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Graph Searching Games and Probabilistic Methods

Graph Searching Games and Probabilistic Methods is the first book that focuses on the intersection of graph searching games and;

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Bridging The Gap Between Graph Edit Distance And Kernel Machines

collection of novel graph kernels related to edit distance, including diffusion kernels, convolution kernels, and random walk kernels. From an;

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Graph Representation Learning

Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry;

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Random Walks and Heat Kernels on Graphs

properties of the graph can be used to establish heat kernel bounds, that is, bounds on the transition probabilities of the random walk, and it;

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Practical Graph Mining with R

Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a do-it-yourself approach;

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Graph Algorithms Practical Examples in Apache Spark and Neo4j

and improving machine learning predictions. You'll walk through hands-on examples that show you how to use graph algorithms in Apache Spark;

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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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Stochastic Optimization Methods: Applications in Engineering and Operations Research

problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under;

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Fractional Dynamics on Networks and Lattices

This book analyzes stochastic processes on networks and regular structures such as lattices by employing the Markovian random walk approach;

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Stochastic Optimization Techniques

respect to random parameter variations, the available statistical information about the random data should be considered already at the planning;

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Distributed Data Fusion for Network-Centric Operations

buildings and defense. Drawing on the work of leading experts around the world, Distributed Data Fusion for Network-Centric Operations examines the;

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Apache Spark Graph Processing

approach A step-by-step guide that will walk you through the key ideas and techniques for processing big graph data at scale, with practical;

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A Graph Theoretic Approach to Heterogeneous Data Clustering

other data types. We model this kind of data using a k-partite graph and partition it by considering it as a fusion of multiple bipartite graphs.;

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Exponential Random Graph Models for Social Networks

Exponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure;

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Exponential Random Graph Models for Social Networks

Exponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure;

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Intelligent Random Walk

social networks. The book opens new horizons for designing prediction models and problem-solving methods based on intelligent random walk;

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Graph Databases

Discover how graph databases can help you manage and query highly connected data. With this practical book, you'll learn how to design and;

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Stochastic Methods for Boundary Value Problems

physics and chemistry. It includes Monte Carlo methods where the random walks live not only on the boundary, but also inside the domain. A variety;

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Discrete Networked Dynamic Systems

deterministic/fixed graphs, switching graphs, and random graphs.;

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On the Influence of Non-Perfect Randomness on Probabilistic Algorithms

probabilistic algorithms are examined on how they are influenced by random numbers that are not independent and uniformly distributed: A randomized;

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An Introduction to Exponential Random Graph Modeling

Explaining the techniques and applications of exponential random graph modeling (ERGM) for social scientists, this is a uniquely;

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Random Walks on Infinite Graphs and Groups

The main theme of this book is the interplay between the behaviour of a class of stochastic processes (random walks) and discrete structure;

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Random Walks on Infinite Graphs and Groups

The main theme of this book is the interplay between the behaviour of a class of stochastic processes (random walks) and discrete structure;

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Mining Graph Data

This text takes a focused and comprehensive look at mining data represented as a graph, with the latest findings and applications in both;

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Nonlinear Time Series Analysis with R

whether highly fluctuating and random appearing data are most likely driven by random or deterministic dynamic forces. It joins the chorus;

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