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Large scale Graph Analysis System Algorithm and Optimization

This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and;

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Large scale Graph Analysis System Algorithm and Optimization

This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and;

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Advances in Metaheuristic Algorithms for Optimal Design of Structures

optimization, Global sensitivity analysis, Tug of War Optimization, Water evaporation optimization, Vibrating System Optimization and Cyclical;

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Advances in Metaheuristic Algorithms for Optimal Design of Structures

optimization, Global sensitivity analysis, Tug of War Optimization, Water evaporation optimization, Vibrating System Optimization and Cyclical;

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Graph-related Optimization and Decision Support Systems

accomplish the feasible set framed by the system constraints. The aim of this book is expose optimization problems that can be expressed as graphs;

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Distributed Machine Learning and Gradient Optimization

effective solution. Focusing on methods that can speed up large-scale gradient optimization through both algorithm optimizations and careful system;

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Large-Scale Graph Processing Using Apache Giraph

describes the fundamental abstractions of the system, its programming models and various techniques for using the system to process graph data at;

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Regularization, Optimization, Kernels, and Support Vector Machines

learning, system identification, domain adaptation, and image processing Tackles large-scale algorithms including conditional gradient methods;

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Regularization, Optimization, Kernels, and Support Vector Machines

Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine;

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Advanced Data Analytics for Power Systems

applications related to power system reliability, efficiency, and security. With topics spanning large-scale and distributed optimization, statistical;

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Advances in Swarm Intelligence

; theories and models of swarm intelligence; ant colony optimization; particle swarm optimization; artificial bee colony algorithms; genetic;

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Genome-Scale Algorithm Design

important biological questions, often for the first time. This book provides an integrated presentation of the fundamental algorithms and data;

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Optimization Problems in Graph Theory

, data analysis, industrial and systems engineering will benefit from the state-of-the-art results presented in modern graph theory and its;

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Parallel Random Search Algorithm

adaptation and partial rollback procedure for constrained pseudo-Boolean optimization problems. Existing optimization algorithms are adapted for the;

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Evolutionary Multi-Criterion Optimization

techniques; hybrid approaches; stopping criteria; parallel EMO models; performance evaluation; test functions and benchmark problems; algorithm;

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Approximability of Optimization Problems through Adiabatic Quantum Computation

optimization problems and can be used for the classical simulation of an AQC algorithm where a Hamiltonian problem is constructed. This construction;

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DNA Algorithm for Integrated Process Planning and Scheduling Problem

conceived in this work to improve the system output in both cost and time frame. The computational prowess of DNA algorithm in preliminary graph;

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Optimization in Renewable Energy Systems

Optimization in Renewable Energy Systems: Recent Perspectives covers all major areas where optimization techniques have been applied to;

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Apache Spark Graph Processing

graph operations tailored to specific needs. * Develop iterative and efficient graph algorithms using message aggregation and Pregel;

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Advances in Swarm Intelligence

optimization; particle swarm optimization; ant colony optimization; fireworks algorithms and brain storm optimization; swarm intelligence algorithms;

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Advances in Swarm Intelligence

optimization; particle swarm optimization; ant colony optimization; fireworks algorithms and brain storm optimization; swarm intelligence algorithms;

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WALCOM: Algorithms and Computation

methodologies, graph algorithms, graph drawing, parallel and distributed algorithms, network optimization.;

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BONUS Algorithm for Large Scale Stochastic Nonlinear Programming Problems

This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale;

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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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Computing and Combinatorics

various topics, including algorithm design, approximation algorithm, graph theory, complexity theory, problem solving, optimization, computational;

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A Derivative-free Two Level Random Search Method for Unconstrained Optimization

new derivative-free optimization methodalgorithm based on randomly generated trial points in specified domains and where the best ones are;

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Self-Regularity

of linear complementarity problems and convex optimization. The algorithm considered can be interpreted as a path-following method or a potential;

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