User Defined Tensor Data Analysis

Author : Bin Dong,Kesheng Wu,Suren Byna
Publisher : Springer Nature
Page : 111 pages
File Size : 51,6 Mb
Release : 2021-09-29
Category : Computers
ISBN : 9783030707507

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User-Defined Tensor Data Analysis by Bin Dong,Kesheng Wu,Suren Byna Pdf

The SpringerBrief introduces FasTensor, a powerful parallel data programming model developed for big data applications. This book also provides a user's guide for installing and using FasTensor. FasTensor enables users to easily express many data analysis operations, which may come from neural networks, scientific computing, or queries from traditional database management systems (DBMS). FasTensor frees users from all underlying and tedious data management tasks, such as data partitioning, communication, and parallel execution. This SpringerBrief gives a high-level overview of the state-of-the-art in parallel data programming model and a motivation for the design of FasTensor. It illustrates the FasTensor application programming interface (API) with an abundance of examples and two real use cases from cutting edge scientific applications. FasTensor can achieve multiple orders of magnitude speedup over Spark and other peer systems in executing big data analysis operations. FasTensor makes programming for data analysis operations at large scale on supercomputers as productively and efficiently as possible. A complete reference of FasTensor includes its theoretical foundations, C++ implementation, and usage in applications. Scientists in domains such as physical and geosciences, who analyze large amounts of data will want to purchase this SpringerBrief. Data engineers who design and develop data analysis software and data scientists, and who use Spark or TensorFlow to perform data analyses, such as training a deep neural network will also find this SpringerBrief useful as a reference tool.

Author : Bin Dong,Kesheng Wu,Suren Byna
Publisher : Unknown
Page : 0 pages
File Size : 45,7 Mb
Release : 2021
Category : Electronic
ISBN : 3030707512

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User-Defined Tensor Data Analysis by Bin Dong,Kesheng Wu,Suren Byna Pdf

Ths SpringerBrief introduces FasTensor, a powerful parallel data programming model developed for big data applications. This book also provides a user's guide for installing and using FasTensor. FasTensor enables users to easily express many data analysis operations, which may come from neural networks, scientific computing, or queries from traditional database management systems (DBMS). FasTensor frees users from all underlying and tedious data management tasks, such as data partitioning, communication, and parallel execution. This SpringerBrief gives a high-level overview of the state-of-the-art in parallel data programming model and a motivation for the design of FasTensor. It illustrates the FasTensor application programming interface (API) with an abundance of examples and two real use cases from cutting edge scientific applications. FasTensor can achieve multiple orders of magnitude speedup over Spark and other peer systems in executing big data analysis operations. FasTensor makes programming for data analysis operations at large scale on supercomputers as productively and efficiently as possible. A complete reference of FasTensor includes its theoretical foundations, C++ implementation, and usage in applications. Scientists in domains such as physical and geosciences, who analyze large amounts of data will want to purchase this SpringerBrief. Data engineers who design and develop data analysis software and data scientists, and who use Spark or TensorFlow to perform data analyses, such as training a deep neural network will also find this SpringerBrief useful as a reference tool.

Author : Yipeng Liu,Jiani Liu,Zhen Long,Ce Zhu
Publisher : Springer Nature
Page : 347 pages
File Size : 48,5 Mb
Release : 2021-08-31
Category : Technology & Engineering
ISBN : 9783030743864

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Tensor Computation for Data Analysis by Yipeng Liu,Jiani Liu,Zhen Long,Ce Zhu Pdf

Tensor is a natural representation for multi-dimensional data, and tensor computation can avoid possible multi-linear data structure loss in classical matrix computation-based data analysis. This book is intended to provide non-specialists an overall understanding of tensor computation and its applications in data analysis, and benefits researchers, engineers, and students with theoretical, computational, technical and experimental details. It presents a systematic and up-to-date overview of tensor decompositions from the engineer's point of view, and comprehensive coverage of tensor computation based data analysis techniques. In addition, some practical examples in machine learning, signal processing, data mining, computer vision, remote sensing, and biomedical engineering are also presented for easy understanding and implementation. These data analysis techniques may be further applied in other applications on neuroscience, communication, psychometrics, chemometrics, biometrics, quantum physics, quantum chemistry, etc. The discussion begins with basic coverage of notations, preliminary operations in tensor computations, main tensor decompositions and their properties. Based on them, a series of tensor-based data analysis techniques are presented as the tensor extensions of their classical matrix counterparts, including tensor dictionary learning, low rank tensor recovery, tensor completion, coupled tensor analysis, robust principal tensor component analysis, tensor regression, logistical tensor regression, support tensor machine, multilinear discriminate analysis, tensor subspace clustering, tensor-based deep learning, tensor graphical model and tensor sketch. The discussion also includes a number of typical applications with experimental results, such as image reconstruction, image enhancement, data fusion, signal recovery, recommendation system, knowledge graph acquisition, traffic flow prediction, link prediction, environmental prediction, weather forecasting, background extraction, human pose estimation, cognitive state classification from fMRI, infrared small target detection, heterogeneous information networks clustering, multi-view image clustering, and deep neural network compression.

Author : Richard Hill,Stuart Berry
Publisher : Springer Nature
Page : 285 pages
File Size : 44,7 Mb
Release : 2021-09-27
Category : Computers
ISBN : 9783030791049

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Guide to Industrial Analytics by Richard Hill,Stuart Berry Pdf

This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.

Author : Nickolay Trendafilov,Michele Gallo
Publisher : Springer Nature
Page : 467 pages
File Size : 46,8 Mb
Release : 2021-09-15
Category : Mathematics
ISBN : 9783030769741

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Multivariate Data Analysis on Matrix Manifolds by Nickolay Trendafilov,Michele Gallo Pdf

This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number of exercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization.

Author : Nathan Gaw
Publisher : Springer Nature
Page : 388 pages
File Size : 45,8 Mb
Release : 2024-05-18
Category : Electronic
ISBN : 9783031530920

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Multimodal and Tensor Data Analytics for Industrial Systems Improvement by Nathan Gaw Pdf

Author : David H. Laidlaw,Joachim Weickert
Publisher : Springer Science & Business Media
Page : 379 pages
File Size : 50,8 Mb
Release : 2009-03-30
Category : Mathematics
ISBN : 9783540883784

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Visualization and Processing of Tensor Fields by David H. Laidlaw,Joachim Weickert Pdf

This book provides researchers an inspirational look at how to process and visualize complicated 2D and 3D images known as tensor fields. With numerous color figures, it details both the underlying mathematics and the applications of tensor fields.

Author : Yipeng Liu
Publisher : Academic Press
Page : 598 pages
File Size : 46,9 Mb
Release : 2021-10-21
Category : Technology & Engineering
ISBN : 9780323859653

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Tensors for Data Processing by Yipeng Liu Pdf

Tensors for Data Processing: Theory, Methods and Applications presents both classical and state-of-the-art methods on tensor computation for data processing, covering computation theories, processing methods, computing and engineering applications, with an emphasis on techniques for data processing. This reference is ideal for students, researchers and industry developers who want to understand and use tensor-based data processing theories and methods. As a higher-order generalization of a matrix, tensor-based processing can avoid multi-linear data structure loss that occurs in classical matrix-based data processing methods. This move from matrix to tensors is beneficial for many diverse application areas, including signal processing, computer science, acoustics, neuroscience, communication, medical engineering, seismology, psychometric, chemometrics, biometric, quantum physics and quantum chemistry. Provides a complete reference on classical and state-of-the-art tensor-based methods for data processing Includes a wide range of applications from different disciplines Gives guidance for their application

Author : Peer-Timo Bremer,Ingrid Hotz,Valerio Pascucci,Ronald Peikert
Publisher : Springer Science & Business
Page : 279 pages
File Size : 44,6 Mb
Release : 2014-04-22
Category : Mathematics
ISBN : 9783319040998

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Topological Methods in Data Analysis and Visualization III by Peer-Timo Bremer,Ingrid Hotz,Valerio Pascucci,Ronald Peikert Pdf

This collection of peer-reviewed conference papers provides comprehensive coverage of cutting-edge research in topological approaches to data analysis and visualization. It encompasses the full range of new algorithms and insights, including fast homology computation, comparative analysis of simplification techniques, and key applications in materials and medical science. The volume also features material on core research challenges such as the representation of large and complex datasets and integrating numerical methods with robust combinatorial algorithms. Reflecting the focus of the TopoInVis 2013 conference, the contributions evince the progress currently being made on finding experimental solutions to open problems in the sector. They provide an inclusive snapshot of state-of-the-art research that enables researchers to keep abreast of the latest developments and provides a foundation for future progress. With papers by some of the world’s leading experts in topological techniques, this volume is a major contribution to the literature in a field of growing importance with applications in disciplines that range from engineering to medicine.

Author : Toshio Sakata,Toshio Sumi,Mitsuhiro Miyazaki
Publisher : Springer
Page : 108 pages
File Size : 45,6 Mb
Release : 2016-03-18
Category : Mathematics
ISBN : 9784431554592

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Algebraic and Computational Aspects of Real Tensor Ranks by Toshio Sakata,Toshio Sumi,Mitsuhiro Miyazaki Pdf

This book provides comprehensive summaries of theoretical (algebraic) and computational aspects of tensor ranks, maximal ranks, and typical ranks, over the real number field. Although tensor ranks have been often argued in the complex number field, it should be emphasized that this book treats real tensor ranks, which have direct applications in statistics. The book provides several interesting ideas, including determinant polynomials, determinantal ideals, absolutely nonsingular tensors, absolutely full column rank tensors, and their connection to bilinear maps and Hurwitz-Radon numbers. In addition to reviews of methods to determine real tensor ranks in details, global theories such as the Jacobian method are also reviewed in details. The book includes as well an accessible and comprehensive introduction of mathematical backgrounds, with basics of positive polynomials and calculations by using the Groebner basis. Furthermore, this book provides insights into numerical methods of finding tensor ranks through simultaneous singular value decompositions.

Author : Fengji Luo,Yunfei Mu,Gaoqi Liang,Yongxi Zhang,Linfeng Yang
Publisher : Frontiers Media SA
Page : 128 pages
File Size : 47,5 Mb
Release : 2023-02-10
Category : Technology & Engineering
ISBN : 9782832514337

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Planning and operation of integrated energy systems with deep integration of pervasive industrial internet-of-things by Fengji Luo,Yunfei Mu,Gaoqi Liang,Yongxi Zhang,Linfeng Yang Pdf

Author : Yuriy I. Dimitrienko
Publisher : Springer Science & Business Media
Page : 690 pages
File Size : 49,7 Mb
Release : 2002-11-30
Category : Mathematics
ISBN : 140201015X

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Tensor Analysis and Nonlinear Tensor Functions by Yuriy I. Dimitrienko Pdf

Tensor Analysis and Nonlinear Tensor Functions embraces the basic fields of tensor calculus: tensor algebra, tensor analysis, tensor description of curves and surfaces, tensor integral calculus, the basis of tensor calculus in Riemannian spaces and affinely connected spaces, - which are used in mechanics and electrodynamics of continua, crystallophysics, quantum chemistry etc. The book suggests a new approach to definition of a tensor in space R3, which allows us to show a geometric representation of a tensor and operations on tensors. Based on this approach, the author gives a mathematically rigorous definition of a tensor as an individual object in arbitrary linear, Riemannian and other spaces for the first time. It is the first book to present a systematized theory of tensor invariants, a theory of nonlinear anisotropic tensor functions and a theory of indifferent tensors describing the physical properties of continua. The book will be useful for students and postgraduates of mathematical, mechanical engineering and physical departments of universities and also for investigators and academic scientists working in continuum mechanics, solid physics, general relativity, crystallophysics, quantum chemistry of solids and material science.

Author : Toshio Sakata
Publisher : Springer
Page : 136 pages
File Size : 46,6 Mb
Release : 2016-02-02
Category : Computers
ISBN : 9784431553878

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Applied Matrix and Tensor Variate Data Analysis by Toshio Sakata Pdf

This book provides comprehensive reviews of recent progress in matrix variate and tensor variate data analysis from applied points of view. Matrix and tensor approaches for data analysis are known to be extremely useful for recently emerging complex and high-dimensional data in various applied fields. The reviews contained herein cover recent applications of these methods in psychology (Chap. 1), audio signals (Chap. 2) , image analysis from tensor principal component analysis (Chap. 3), and image analysis from decomposition (Chap. 4), and genetic data (Chap. 5) . Readers will be able to understand the present status of these techniques as applicable to their own fields. In Chapter 5 especially, a theory of tensor normal distributions, which is a basic in statistical inference, is developed, and multi-way regression, classification, clustering, and principal component analysis are exemplified under tensor normal distributions. Chapter 6 treats one-sided tests under matrix variate and tensor variate normal distributions, whose theory under multivariate normal distributions has been a popular topic in statistics since the books of Barlow et al. (1972) and Robertson et al. (1988). Chapters 1, 5, and 6 distinguish this book from ordinary engineering books on these topics.

Author : Xian-Da Zhang
Publisher : Cambridge University Press
Page : 761 pages
File Size : 54,6 Mb
Release : 2017-10-05
Category : Computers
ISBN : 9781108417419

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Matrix Analysis and Applications by Xian-Da Zhang Pdf

The theory, methods and applications of matrix analysis are presented here in a novel theoretical framework.

Author : Edoardo Angelo Di Napoli,Paolo Bientinesi,Jiajia Li,André Uschmajew
Publisher : Frontiers Media SA
Page : 192 pages
File Size : 49,9 Mb
Release : 2022-11-08
Category : Science
ISBN : 9782832504253

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High-Performance Tensor Computations in Scientific Computing and Data Science by Edoardo Angelo Di Napoli,Paolo Bientinesi,Jiajia Li,André Uschmajew Pdf