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Author : Ake Bjorck
Publisher :
ISBN 13 : 9780608163819
Total Pages : 412 pages
Book Rating : 4.1/5 (638 download)
Download or read book Large Scale Matrix Problems written by Ake Bjorck and published by . This book was released on with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yousef Saad
Publisher : SIAM
ISBN 13 : 9781611970739
Total Pages : 292 pages
Book Rating : 4.9/5 (77 download)
Download or read book Numerical Methods for Large Eigenvalue Problems written by Yousef Saad and published by SIAM. This book was released on 2011-01-01 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This revised edition discusses numerical methods for computing eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods that are applicable for solving matrix eigenvalue problems that arise in various engineering and scientific applications. Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest, and adapting the Notes and References section. Significant changes have been made to Chapters 6 through 8, which describe algorithms and their implementations and now include topics such as the implicit restart techniques, the Jacobi-Davidson method, and automatic multilevel substructuring.
Author : Åke Björck
Publisher : North-Holland
ISBN 13 :
Total Pages : 426 pages
Book Rating : 4.3/5 (91 download)
Download or read book Large Scale Matrix Problems written by Åke Björck and published by North-Holland. This book was released on 1981 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : J. Cullum
Publisher : Elsevier
ISBN 13 : 9780080872384
Total Pages : 329 pages
Book Rating : 4.8/5 (723 download)
Download or read book Large Scale Eigenvalue Problems written by J. Cullum and published by Elsevier. This book was released on 1986-01-01 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Results of research into large scale eigenvalue problems are presented in this volume. The papers fall into four principal categories: novel algorithms for solving large eigenvalue problems, novel computer architectures, computationally-relevant theoretical analyses, and problems where large scale eigenelement computations have provided new insight.
Author : John Gilbert
Publisher :
ISBN 13 : 9781383025446
Total Pages : 0 pages
Book Rating : 4.0/5 (254 download)
Download or read book Large-scale Matrix Problems and the Numerical Solution of Partial Differential Equations written by John Gilbert and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Containing contributions from the 5th SERC Summer School in Numerical Analysis, held at Lancaster University in 1992, this volume covers a wide range of research developments in numerical analysis.
Author : Peter Arbenz
Publisher : Nova Publishers
ISBN 13 : 9781560725947
Total Pages : 228 pages
Book Rating : 4.7/5 (259 download)
Download or read book High Performance Algorithms for Structured Matrix Problems written by Peter Arbenz and published by Nova Publishers. This book was released on 1998 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprises 10 contributions that summarize the state of the art in the areas of high performance solutions of structured linear systems and structured eigenvalue and singular-value problems. Topics covered range from parallel solvers for sparse or banded linear systems to parallel computation of eigenvalues and singular values of tridiagonal and bidiagonal matrices. Specific paper topics include: the stable parallel solution of general narrow banded linear systems; efficient algorithms for reducing banded matrices to bidiagonal and tridiagonal form; a numerical comparison of look-ahead Levinson and Schur algorithms for non-Hermitian Toeplitz systems; and parallel CG-methods automatically optimized for PC and workstation clusters. Annotation copyrighted by Book News, Inc., Portland, OR
Author : Vladimir Tsurkov
Publisher : Springer Science & Business Media
ISBN 13 : 1475732430
Total Pages : 322 pages
Book Rating : 4.4/5 (757 download)
Download or read book Large-scale Optimization written by Vladimir Tsurkov and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decomposition methods aim to reduce large-scale problems to simpler problems. This monograph presents selected aspects of the dimension-reduction problem. Exact and approximate aggregations of multidimensional systems are developed and from a known model of input-output balance, aggregation methods are categorized. The issues of loss of accuracy, recovery of original variables (disaggregation), and compatibility conditions are analyzed in detail. The method of iterative aggregation in large-scale problems is studied. For fixed weights, successively simpler aggregated problems are solved and the convergence of their solution to that of the original problem is analyzed. An introduction to block integer programming is considered. Duality theory, which is widely used in continuous block programming, does not work for the integer problem. A survey of alternative methods is presented and special attention is given to combined methods of decomposition. Block problems in which the coupling variables do not enter the binding constraints are studied. These models are worthwhile because they permit a decomposition with respect to primal and dual variables by two-level algorithms instead of three-level algorithms. Audience: This book is addressed to specialists in operations research, optimization, and optimal control.
Author : H. Amman
Publisher : Springer Science & Business Media
ISBN 13 : 9401131627
Total Pages : 170 pages
Book Rating : 4.4/5 (11 download)
Download or read book Computational Economics and Econometrics written by H. Amman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of Computational Economics is a fast growing area. Due to the limitations in analytical modeling, more and more researchers apply numerical methods as a means of problem solving. In tum these quantitative results can be used to make qualitative statements. This volume of the Advanced Series in Theoretical and Applied and Econometrics comprises a selected number of papers in the field of computational economics presented at the Annual Meeting of the Society Economic Dynamics and Control held in Minneapolis, June 1990. The volume covers ten papers dealing with computational issues in Econo metrics, Economics and Optimization. The first five papers in these proceedings are dedicated to numerical issues in econometric estimation. The following three papers are concerned with computational issues in model solving and optimization. The last two papers highlight some numerical techniques for solving micro models. We are sure that Computational Economics will become an important new trend in Economics in the coming decade. Hopefully this volume can be one of the first contributions highlighting this new trend. The Editors H.M. Amman et a1. (eds), Computational Economics and Econometrics, vii. © 1992 Kluwer Academic Publishers. PART ONE ECONOMETRICS LIKELIHOOD EVALUATION FOR DYNAMIC LATENT VARIABLES 1 MODELS DAVID F. HENDRY Nuffield College, Oxford, U.K. and JEAN-FRANc;mS RICHARD ISDS, Pittsburgh University, Pittsburgh, PA, U.S.A.
Author : Vinod Kumar Chauhan
Publisher : CRC Press
ISBN 13 : 1000505537
Total Pages : 177 pages
Book Rating : 4.0/5 (5 download)
Download or read book Stochastic Optimization for Large-scale Machine Learning written by Vinod Kumar Chauhan and published by CRC Press. This book was released on 2021-11-18 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advancements in the technology and availability of data sources have led to the `Big Data' era. Working with large data offers the potential to uncover more fine-grained patterns and take timely and accurate decisions, but it also creates a lot of challenges such as slow training and scalability of machine learning models. One of the major challenges in machine learning is to develop efficient and scalable learning algorithms, i.e., optimization techniques to solve large scale learning problems. Stochastic Optimization for Large-scale Machine Learning identifies different areas of improvement and recent research directions to tackle the challenge. Developed optimisation techniques are also explored to improve machine learning algorithms based on data access and on first and second order optimisation methods. Key Features: Bridges machine learning and Optimisation. Bridges theory and practice in machine learning. Identifies key research areas and recent research directions to solve large-scale machine learning problems. Develops optimisation techniques to improve machine learning algorithms for big data problems. The book will be a valuable reference to practitioners and researchers as well as students in the field of machine learning.
Author : Sabine Mondie
Publisher : Elsevier
ISBN 13 : 9780080441313
Total Pages : 780 pages
Book Rating : 4.4/5 (413 download)
Download or read book System, Structure and Control 2004 written by Sabine Mondie and published by Elsevier. This book was released on 2005-05-11 with total page 780 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gene Howard Golub
Publisher :
ISBN 13 : 9780801837395
Total Pages : 694 pages
Book Rating : 4.8/5 (373 download)
Download or read book Matrix Computations written by Gene Howard Golub and published by . This book was released on 1996 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Revised and updated, the third edition of Golub and Van Loan's classic text in computer science provides essential information about the mathematical background and algorithmic skills required for the production of numerical software. This new edition includes thoroughly revised chapters on matrix multiplication problems and parallel matrix computations, expanded treatment of CS decomposition, an updated overview of floating point arithmetic, a more accurate rendition of the modified Gram-Schmidt process, and new material devoted to GMRES, QMR, and other methods designed to handle the sparse unsymmetric linear system problem.
Author : Vipin Kumar
Publisher : Springer Science & Business Media
ISBN 13 : 3540401555
Total Pages : 1093 pages
Book Rating : 4.5/5 (44 download)
Download or read book Computational Science and Its Applications - ICCSA 2003 written by Vipin Kumar and published by Springer Science & Business Media. This book was released on 2003-05-08 with total page 1093 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set, LNCS 2667, LNCS 2668, and LNCS 2669, constitutes the refereed proceedings of the International Conference on Computational Science and Its Applications, ICCSA 2003, held in Montreal, Canada, in May 2003. The three volumes present more than 300 papers and span the whole range of computational science from foundational issues in computer science and mathematics to advanced applications in virtually all sciences making use of computational techniques. The proceedings give a unique account of recent results in computational science.
Author : Matheus Cavalcante
Publisher : BoD – Books on Demand
ISBN 13 : 3866288018
Total Pages : 224 pages
Book Rating : 4.8/5 (662 download)
Download or read book Fighting Back the Von Neumann Bottleneck with Small- and Large-Scale Vector Microprocessors written by Matheus Cavalcante and published by BoD – Books on Demand. This book was released on 2023-08-24 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: In his seminal Turing Award Lecture, Backus discussed the issues stemming from the word-at-a-time style of programming inherited from the von Neumann computer. More than forty years later, computer architects must be creative to amortize the von Neumann Bottleneck (VNB) associated with fetching and decoding instructions which only keep the datapath busy for a very short period of time. In particular, vector processors promise to be one of the most efficient architectures to tackle the VNB, by amortizing the energy overhead of instruction fetching and decoding over several chunks of data. This work explores vector processing as an option to build small and efficient processing elements for large-scale clusters of cores sharing access to tightly-coupled L1 memory
Author : Peter Bühlmann
Publisher : CRC Press
ISBN 13 : 1482249081
Total Pages : 480 pages
Book Rating : 4.4/5 (822 download)
Download or read book Handbook of Big Data written by Peter Bühlmann and published by CRC Press. This book was released on 2016-02-22 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Big Data provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in statistics and computer science, this handbook presents a carefully curated collection of techniques from both industry and academia. Thus, the text instills a working understanding of key statistical
Author : Thomas Frederick Coleman
Publisher : SIAM
ISBN 13 : 9780898712681
Total Pages : 278 pages
Book Rating : 4.7/5 (126 download)
Download or read book Large-scale Numerical Optimization written by Thomas Frederick Coleman and published by SIAM. This book was released on 1990-01-01 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers from a workshop held at Cornell University, Oct. 1989, and sponsored by Cornell's Mathematical Sciences Institute. Annotation copyright Book News, Inc. Portland, Or.
Author :
Publisher :
ISBN 13 :
Total Pages : 190 pages
Book Rating : 4.3/5 (243 download)
Download or read book Scientific Information Bulletin written by and published by . This book was released on 1993 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ashok N. Srivastava
Publisher : CRC Press
ISBN 13 : 1315354462
Total Pages : 354 pages
Book Rating : 4.3/5 (153 download)
Download or read book Large-Scale Machine Learning in the Earth Sciences written by Ashok N. Srivastava and published by CRC Press. This book was released on 2017-08-01 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the Foreword: "While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in the early stages. This book, edited by Ashok Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an outstanding resource for anyone interested in the opportunities and challenges for the machine learning community in analyzing these data sets to answer questions of urgent societal interest...I hope that this book will inspire more computer scientists to focus on environmental applications, and Earth scientists to seek collaborations with researchers in machine learning and data mining to advance the frontiers in Earth sciences." --Vipin Kumar, University of Minnesota Large-Scale Machine Learning in the Earth Sciences provides researchers and practitioners with a broad overview of some of the key challenges in the intersection of Earth science, computer science, statistics, and related fields. It explores a wide range of topics and provides a compilation of recent research in the application of machine learning in the field of Earth Science. Making predictions based on observational data is a theme of the book, and the book includes chapters on the use of network science to understand and discover teleconnections in extreme climate and weather events, as well as using structured estimation in high dimensions. The use of ensemble machine learning models to combine predictions of global climate models using information from spatial and temporal patterns is also explored. The second part of the book features a discussion on statistical downscaling in climate with state-of-the-art scalable machine learning, as well as an overview of methods to understand and predict the proliferation of biological species due to changes in environmental conditions. The problem of using large-scale machine learning to study the formation of tornadoes is also explored in depth. The last part of the book covers the use of deep learning algorithms to classify images that have very high resolution, as well as the unmixing of spectral signals in remote sensing images of land cover. The authors also apply long-tail distributions to geoscience resources, in the final chapter of the book.
