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Large-Scale Graph Analysis: System, Algorithm and Optimization, Shao Yingxia, Cui Bin, Chen Lei


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Автор: Shao Yingxia, Cui Bin, Chen Lei
Название:  Large-Scale Graph Analysis: System, Algorithm and Optimization
ISBN: 9789811539275
Издательство: Springer
Классификация:






ISBN-10: 9811539278
Обложка/Формат: Hardcover
Страницы: 146
Вес: 0.40 кг.
Дата издания: 02.07.2020
Серия: Big data management
Язык: English
Издание: 1st ed. 2020
Иллюстрации: 30 illustrations, color; 48 illustrations, black and white; xiii, 146 p. 78 illus., 30 illus. in color.
Размер: 23.39 x 15.60 x 1.12 cm
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently.


Robust and Online Large-Scale Optimization

Автор: Ravindra K. Ahuja; Rolf H. M?hring; Christos Zarol
Название: Robust and Online Large-Scale Optimization
ISBN: 3642054641 ISBN-13(EAN): 9783642054648
Издательство: Springer
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Цена: 12577.00 р.
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Описание: Scheduled transportation networks give rise to complex and large-scale network optimization problems requiring innovative solution techniques and ideas from mathematical optimization and theoretical computer science. This book features papers on this topic.

Large-Scale PDE-Constrained Optimization in Applications

Автор: Subhendu Bikash Hazra
Название: Large-Scale PDE-Constrained Optimization in Applications
ISBN: 3642263887 ISBN-13(EAN): 9783642263880
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This book develops mathematical methods and algorithms that lead to efficient and high performance computational techniques to solve simulation based optimization problems in real-life applications.

Functional Analysis and Optimization Methods in Hadron Physics

Автор: Irinel Caprini
Название: Functional Analysis and Optimization Methods in Hadron Physics
ISBN: 3030189473 ISBN-13(EAN): 9783030189471
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book begins with a brief historical review of the early applications of standard dispersion relations in particle physics. It then presents the modern perspective within the Standard Model, emphasizing the relation of analyticity together with alternative tools applied to strong interactions, such as perturbative and lattice quantum chromodynamics (QCD), as well as chiral perturbation theory. The core of the book argues that, in order to improve the prediction of specific hadronic observables, it is often necessary to resort to methods of complex analysis more sophisticated than the simple Cauchy integral. Accordingly, a separate mathematical chapter is devoted to solving several functional analysis optimization problems. Their applications to physical amplitudes and form factors are discussed in the following chapters, which also demonstrate how to merge the analytic approach with statistical analysis tools. Given its scope, the book offers a valuable guide for researchers working in precision hadronic physics, as well as graduate students who are new to the field.

Remote compositional analysis : techniques for understanding spectroscopy, mineralogy, and geochemistry of planetary surfaces

Автор: Janice L. Bishop, James F. Bell III, Jeffrey E. Mo
Название: Remote compositional analysis : techniques for understanding spectroscopy, mineralogy, and geochemistry of planetary surfaces
ISBN: 110718620X ISBN-13(EAN): 9781107186200
Издательство: Cambridge Academ
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Цена: 16315.00 р.
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Описание: This book provides a comprehensive overview of the theory and practical applications of spectroscopic, mineralogical, and geochemical techniques used in planetary remote sensing. It describes state-of-the-art developments in analyzing the chemistry and mineralogy of the surfaces of planets, moons, asteroids, and comets.

Cluster Analysis for Data Mining and System Identification

Автор: Abonyi JГЎnos, Feil BalГЎzs
Название: Cluster Analysis for Data Mining and System Identification
ISBN: 3764379871 ISBN-13(EAN): 9783764379872
Издательство: Springer
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Цена: 13969.00 р.
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Описание: This book presents new approaches to data mining and system identification. Algorithmsthat can be used for the clustering of data have been overviewed. New techniques andtools are presented for the clustering, classification, regression and visualization ofcomplex datasets. Special attention is given to the analysis of historical process data,tailored algorithms are presented for the data driven modeling of dynamical systems,determining the model order of nonlinear input-output black box models, and thesegmentation of multivariate time-series. The main methods and techniques areillustrated through several simulated and real-world applications from data mining andprocess engineering practice.The books is aimed primarily at practitioners, researches, and professionals in statistics,data mining, business intelligence, and systems engineering, but it is also accessible tograduate and undergraduate students in applied mathematics, computer science, electricaland process engineering. Familiarity with the basics of system identification and fuzzysystems is helpful but not required.

Large-Scale PDE-Constrained Optimization in Applications

Автор: Subhendu Bikash Hazra
Название: Large-Scale PDE-Constrained Optimization in Applications
ISBN: 3642015018 ISBN-13(EAN): 9783642015014
Издательство: Springer
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Цена: 18167.00 р.
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Описание: With continuous development of modern computing hardware and applicable - merical methods, computational ?uid dynamics (CFD) has reached certain level of maturity so that it is being used routinely by scientists and engineers for ?uid ?ow analysis.

Automated Machine Learning: Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms

Автор: Masood Adnan
Название: Automated Machine Learning: Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms
ISBN: 1800567685 ISBN-13(EAN): 9781800567689
Издательство: Неизвестно
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Цена: 9010.00 р.
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Описание:

Get to grips with automated machine learning and adopt a hands-on approach to AutoML implementation and associated methodologies


Key Features:

  • Get up to speed with AutoML using OSS, Azure, AWS, GCP, or any platform of your choice
  • Eliminate mundane tasks in data engineering and reduce human errors in machine learning models
  • Find out how you can make machine learning accessible for all users to promote decentralized processes


Book Description:

Every machine learning engineer deals with systems that have hyperparameters, and the most basic task in automated machine learning (AutoML) is to automatically set these hyperparameters to optimize performance. The latest deep neural networks have a wide range of hyperparameters for their architecture, regularization, and optimization, which can be customized effectively to save time and effort.


This book reviews the underlying techniques of automated feature engineering, model and hyperparameter tuning, gradient-based approaches, and much more. You'll discover different ways of implementing these techniques in open source tools and then learn to use enterprise tools for implementing AutoML in three major cloud service providers: Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform. As you progress, you'll explore the features of cloud AutoML platforms by building machine learning models using AutoML. The book will also show you how to develop accurate models by automating time-consuming and repetitive tasks in the machine learning development lifecycle.


By the end of this machine learning book, you'll be able to build and deploy AutoML models that are not only accurate, but also increase productivity, allow interoperability, and minimize feature engineering tasks.


What You Will Learn:

  • Explore AutoML fundamentals, underlying methods, and techniques
  • Assess AutoML aspects such as algorithm selection, auto featurization, and hyperparameter tuning in an applied scenario
  • Find out the difference between cloud and operations support systems (OSS)
  • Implement AutoML in enterprise cloud to deploy ML models and pipelines
  • Build explainable AutoML pipelines with transparency
  • Understand automated feature engineering and time series forecasting
  • Automate data science modeling tasks to implement ML solutions easily and focus on more complex problems


Who this book is for:

Citizen data scientists, machine learning developers, artificial intelligence enthusiasts, or anyone looking to automatically build machine learning models using the features offered by open source tools, Microsoft Azure Machine Learning, AWS, and Google Cloud Platform will find this book useful. Beginner-level knowledge of building ML models is required to get the best out of this book. Prior experience in using Enterprise cloud is beneficial.

Engineering Mathematics II: Algebraic, Stochastic and Analysis Structures for Networks, Data Classification and Optimization

Автор: Silvestrov Sergei, Rančic Milica
Название: Engineering Mathematics II: Algebraic, Stochastic and Analysis Structures for Networks, Data Classification and Optimization
ISBN: 3319824996 ISBN-13(EAN): 9783319824994
Издательство: Springer
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Цена: 20962.00 р.
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Описание:

1 Classification of Low Dimensional 3-Lie Superalgebras: V. Abramov and P. Lдtt.- 2 Semi-Commutative Galois Extension and Reduced Quantum Plane: V. Abramov and Md. Raknuzzaman.- 3 Valued Custom Skew Fields with Generalised PBW Property from Power Series Construction: L. Hellstrцm.- 4 Computing Burchnall-Chaundy Polynomials with Determinants: J. Richter and S. Silvestrov.- 5 Centralizers and Pseudo-Degree Functions: J. Richter.- 6 Asymptotic Expansions for Moment Functionals of Perturbed Discrete Time Semi-Markov Processes: M. Petersson.- 7 Asymptotics for Quasi-Stationary Distributions of Perturbed Discrete Time Semi-Markov Processes: M. Petersson.- 8 PageRank, a Look at Small Changes in a Line of Nodes and the Complete Graph: Ch. Engstrцm and S. Silvestrov.- 9 PageRank, Connecting a Line of Nodes with a Complete Graph: Ch. Engstrцm and S. Silvestrov.- 10 Output Rate Variation Problem: Some Heuristic Paradigms and Dynamic Programming: G.B. Thapa and S. Silvestrov.- 11 Lp-Boundedness of Two Singular Integral Operators of Convolution Type: J. Musonda and S. Kaijser.- 12 Crossed Product Algebras for Piece-Wise Constant Functions: A.B. Tumwesigye et al.- 13 Linear Classification of Data with Support Vector Machines and Generalized Support Vector Machines: Xiaomin Qi et al.- 14 Linear and Nonlinear Classifiers of Data with Support Vector Machines and Generalized Support Vector Machines: X. Qi et al.- 15 Common Fixed Points of Weakly Commuting Multivalued Mappings on a Domain of Sets Endowed with Directed Graph: S. Silvestrov and T. Nazir.- 16 Common Fixed Point Results for Family of Generalized Multivalued F-contraction Mappings in Ordered Metric Spaces: T. Nazir and S. Silvestrov.

Optimization and Data Analysis in Biomedical Informatics

Автор: Panos M. Pardalos; Thomas F. Coleman; Petros Xanth
Название: Optimization and Data Analysis in Biomedical Informatics
ISBN: 1489999663 ISBN-13(EAN): 9781489999665
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This work is targeted to applied mathematicians, computer scientists, industrial engineers, and clinical scientists who are interested in exploring emerging and fascinating interdisciplinary topics of research.

Optimization Techniques for Problem Solving in Uncertainty

Автор: Surafel Luleseged Tilahun, Jean Medard T. Ngnotchouye
Название: Optimization Techniques for Problem Solving in Uncertainty
ISBN: 1522550917 ISBN-13(EAN): 9781522550914
Издательство: Mare Nostrum (Eurospan)
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Цена: 28413.00 р.
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Описание: When it comes to optimization techniques, in some cases, the available information from real models may not be enough to construct either a probability distribution or a membership function for problem solving. In such cases, there are various theories that can be used to quantify the uncertain aspects.Optimization Techniques for Problem Solving in Uncertainty is a scholarly reference resource that looks at uncertain aspects involved in different disciplines and applications. Featuring coverage on a wide range of topics including uncertain preference, fuzzy multilevel programming, and metaheuristic applications, this book is geared towards engineers, managers, researchers, and post-graduate students seeking emerging research in the field of optimization.

Advances in System Optimization and Control

Автор: Sri Niwas Singh; Fushuan Wen; Monika Jain
Название: Advances in System Optimization and Control
ISBN: 9811344752 ISBN-13(EAN): 9789811344756
Издательство: Springer
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Цена: 27950.00 р.
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Описание: This book comprises select proceedings of the International Conference on Advancement in Energy, Drives, and Control. It covers frontier topics in optimization and control. It covers applications of optimization processes in areas such as computer architecture, communication systems, system optimization, signal processing, fluid dynamics and process control. This book is of use to researchers, professionals, and students from across engineering disciplines.

Mastering Spark with R: The Complete Guide to Large-Scale Analysis and Modeling

Название: Mastering Spark with R: The Complete Guide to Large-Scale Analysis and Modeling
ISBN: 149204637X ISBN-13(EAN): 9781492046370
Издательство: Wiley
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Цена: 7126.00 р.
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Описание: With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems.


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