Download or read book Scalable Algorithms for Contact Problems written by Zdeněk Dostál and published by Springer Nature. This book was released on 2023-11-29 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive treatment of recently developed scalable algorithms for solving multibody contact problems of linear elasticity. The brand-new feature of these algorithms is their theoretically supported numerical scalability (i.e., asymptotically linear complexity) and parallel scalability demonstrated in solving problems discretized by billions of degrees of freedom. The theory covers solving multibody frictionless contact problems, contact problems with possibly orthotropic Tresca’s friction, and transient contact problems. In addition, it also covers BEM discretization, treating jumping coefficients, floating bodies, mortar non-penetration conditions, etc. This second edition includes updated content, including a new chapter on hybrid domain decomposition methods for huge contact problems. Furthermore, new sections describe the latest algorithm improvements, e.g., the fast reconstruction of displacements, the adaptive reorthogonalization of dual constraints, and an updated chapter on parallel implementation. Several chapters are extended to give an independent exposition of classical bounds on the spectrum of mass and dual stiffness matrices, a benchmark for Coulomb orthotropic friction, details of discretization, etc. The exposition is divided into four parts, the first of which reviews auxiliary linear algebra, optimization, and analysis. The most important algorithms and optimality results are presented in the third chapter. The presentation includes continuous formulation, discretization, domain decomposition, optimality results, and numerical experiments. The final part contains extensions to contact shape optimization, plasticity, and HPC implementation. Graduate students and researchers in mechanical engineering, computational engineering, and applied mathematics will find this book of great value and interest.
Download or read book Scalable Algorithms for Contact Problems written by Zdeněk Dostál and published by Springer. This book was released on 2017-01-25 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive and self-contained treatment of the authors’ newly developed scalable algorithms for the solutions of multibody contact problems of linear elasticity. The brand new feature of these algorithms is theoretically supported numerical scalability and parallel scalability demonstrated on problems discretized by billions of degrees of freedom. The theory supports solving multibody frictionless contact problems, contact problems with possibly orthotropic Tresca’s friction, and transient contact problems. It covers BEM discretization, jumping coefficients, floating bodies, mortar non-penetration conditions, etc. The exposition is divided into four parts, the first of which reviews appropriate facets of linear algebra, optimization, and analysis. The most important algorithms and optimality results are presented in the third part of the volume. The presentation is complete, including continuous formulation, discretization, decomposition, optimality results, and numerical experiments. The final part includes extensions to contact shape optimization, plasticity, and HPC implementation. Graduate students and researchers in mechanical engineering, computational engineering, and applied mathematics, will find this book of great value and interest.
Download or read book Scalable Algorithms for Data and Network Analysis written by Shang-Hua Teng and published by . This book was released on 2016-05-04 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the age of Big Data, efficient algorithms are in high demand. It is also essential that efficient algorithms should be scalable. This book surveys a family of algorithmic techniques for the design of scalable algorithms. These techniques include local network exploration, advanced sampling, sparsification, and geometric partitioning.
Download or read book Scalable Fuzzy Algorithms for Data Management and Analysis Methods and Design written by Laurent, Anne and published by IGI Global. This book was released on 2009-10-31 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents up-to-date techniques for addressing data management problems with logic and memory use"--Provided by publisher.
Download or read book Algorithms for Data Science written by Brian Steele and published by Springer. This book was released on 2016-12-25 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook on practical data analytics unites fundamental principles, algorithms, and data. Algorithms are the keystone of data analytics and the focal point of this textbook. Clear and intuitive explanations of the mathematical and statistical foundations make the algorithms transparent. But practical data analytics requires more than just the foundations. Problems and data are enormously variable and only the most elementary of algorithms can be used without modification. Programming fluency and experience with real and challenging data is indispensable and so the reader is immersed in Python and R and real data analysis. By the end of the book, the reader will have gained the ability to adapt algorithms to new problems and carry out innovative analyses. This book has three parts:(a) Data Reduction: Begins with the concepts of data reduction, data maps, and information extraction. The second chapter introduces associative statistics, the mathematical foundation of scalable algorithms and distributed computing. Practical aspects of distributed computing is the subject of the Hadoop and MapReduce chapter.(b) Extracting Information from Data: Linear regression and data visualization are the principal topics of Part II. The authors dedicate a chapter to the critical domain of Healthcare Analytics for an extended example of practical data analytics. The algorithms and analytics will be of much interest to practitioners interested in utilizing the large and unwieldly data sets of the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System.(c) Predictive Analytics Two foundational and widely used algorithms, k-nearest neighbors and naive Bayes, are developed in detail. A chapter is dedicated to forecasting. The last chapter focuses on streaming data and uses publicly accessible data streams originating from the Twitter API and the NASDAQ stock market in the tutorials. This book is intended for a one- or two-semester course in data analytics for upper-division undergraduate and graduate students in mathematics, statistics, and computer science. The prerequisites are kept low, and students with one or two courses in probability or statistics, an exposure to vectors and matrices, and a programming course will have no difficulty. The core material of every chapter is accessible to all with these prerequisites. The chapters often expand at the close with innovations of interest to practitioners of data science. Each chapter includes exercises of varying levels of difficulty. The text is eminently suitable for self-study and an exceptional resource for practitioners.
Download or read book Scalable Algorithms written by Vassil Alexandrov and published by CRC Press. This book was released on 2016-10-15 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Novel scalable scientific algorithms are needed to enable key science applications and to exploit the computational power of largescale systems. This is especially true for the current tier of leading petascale machines and the road to exascale computing as HPC systems continue to scale up in compute node and processor core count. These extreme-scale systems require novel scientific algorithms to hide network and memory latency, have very high computation/communication overlap, have minimal communication, and no synchronization points. Authored by two of the leading experts in this area, this book focuses on the latest advances in scalable algorithms for large scale systems.
Download or read book Scalable Algorithms for Boolean Satisfiability Enabled by Problem Structure written by Fadi Ahmed Aloul and published by . This book was released on 2003 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Building Scalable Web Sites written by Cal Henderson and published by "O'Reilly Media, Inc.". This book was released on 2006-05-16 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building, scaling, and optimizing the next generation of Web applications.
Download or read book Scalable Optimization via Probabilistic Modeling written by Martin Pelikan and published by Springer Science & Business Media. This book was released on 2006-09-25 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: I’m not usually a fan of edited volumes. Too often they are an incoherent hodgepodge of remnants, renegades, or rejects foisted upon an unsuspecting reading public under a misleading or fraudulent title. The volume Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications is a worthy addition to your library because it succeeds on exactly those dimensions where so many edited volumes fail. For example, take the title, Scalable Optimization via Probabilistic M- eling: From Algorithms to Applications. You need not worry that you’re going to pick up this book and ?nd stray articles about anything else. This book focuseslikealaserbeamononeofthehottesttopicsinevolutionary compu- tion over the last decade or so: estimation of distribution algorithms (EDAs). EDAs borrow evolutionary computation’s population orientation and sel- tionism and throw out the genetics to give us a hybrid of substantial power, elegance, and extensibility. The article sequencing in most edited volumes is hard to understand, but from the get go the editors of this volume have assembled a set of articles sequenced in a logical fashion. The book moves from design to e?ciency enhancement and then concludes with relevant applications. The emphasis on e?ciency enhancement is particularly important, because the data-mining perspectiveimplicitinEDAsopensuptheworldofoptimizationtonewme- ods of data-guided adaptation that can further speed solutions through the construction and utilization of e?ective surrogates, hybrids, and parallel and temporal decompositions.
Download or read book Mastering Data Mining written by Cybellium Ltd and published by Cybellium Ltd. This book was released on with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncover Hidden Insights and Patterns in Your Data Are you ready to delve into the fascinating realm of data mining? "Mastering Data Mining" is your ultimate guide to unlocking the potential of extracting hidden insights and patterns from your data. Whether you're a data scientist aiming to uncover valuable information or a business professional seeking to make informed decisions, this book equips you with the knowledge and techniques to master the art of data mining. Key Features: 1. Journey into Data Mining: Immerse yourself in the world of data mining, understanding its significance, methodologies, and applications. Build a solid foundation that empowers you to extract meaningful insights from complex datasets. 2. Data Exploration and Preparation: Master the art of data exploration and preparation. Learn how to clean, transform, and preprocess data for effective mining. 3. Exploratory Data Analysis: Delve into exploratory data analysis techniques. Explore visualization, statistical summaries, and data profiling to gain a deeper understanding of your dataset. 4. Supervised Learning Techniques: Uncover the power of supervised learning techniques. Learn how to build predictive models for classification and regression tasks, enabling you to make accurate predictions. 5. Unsupervised Learning and Clustering: Discover unsupervised learning and clustering methods. Explore techniques for grouping similar data points and identifying hidden patterns without predefined labels. 6. Association Rule Mining: Master association rule mining for uncovering relationships in data. Learn how to identify frequent itemsets and extract valuable associations. 7. Text and Web Mining: Explore text and web mining techniques. Learn how to extract insights from textual data and discover patterns in web-based information. 8. Time Series Mining: Delve into time series mining for analyzing sequential data. Learn how to forecast trends, identify anomalies, and make predictions based on temporal patterns. 9. Data Mining Tools and Algorithms: Uncover a range of data mining tools and algorithms. Explore classic algorithms and modern techniques for various data mining tasks. 10. Real-World Applications: Gain insights into real-world use cases of data mining across industries. From customer segmentation to fraud detection, explore how organizations leverage data mining for strategic advantage. Who This Book Is For: "Mastering Data Mining" is an indispensable resource for data scientists, analysts, and business professionals who want to excel in uncovering insights from data. Whether you're new to data mining or seeking advanced techniques, this book will guide you through the intricacies and empower you to harness the full potential of data mining. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com
Download or read book Annual Review Of Scalable Computing written by Chung Kwong Yuen and published by World Scientific. This book was released on 2004-06-07 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents original articles, reviewing various aspects of scalable computing. Parallel computation with optically interconnected systems makes its first appearance, and further work on distributed Java is also reported. Optimizing data grids and group communication are studied in two analytical chapters. The comprehensive treatment of these topics adds further to the current literature.
Download or read book Optimal Quadratic Programming Algorithms written by Zdenek Dostál and published by Springer Science & Business Media. This book was released on 2009-04-03 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quadratic programming (QP) is one advanced mathematical technique that allows for the optimization of a quadratic function in several variables in the presence of linear constraints. This book presents recently developed algorithms for solving large QP problems and focuses on algorithms which are, in a sense optimal, i.e., they can solve important classes of problems at a cost proportional to the number of unknowns. For each algorithm presented, the book details its classical predecessor, describes its drawbacks, introduces modifications that improve its performance, and demonstrates these improvements through numerical experiments. This self-contained monograph can serve as an introductory text on quadratic programming for graduate students and researchers. Additionally, since the solution of many nonlinear problems can be reduced to the solution of a sequence of QP problems, it can also be used as a convenient introduction to nonlinear programming.
Download or read book Machine Learning and Knowledge Discovery in Databases written by Ulf Brefeld and published by Springer Nature. This book was released on 2020-05-01 with total page 799 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume proceedings LNAI 11906 – 11908 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, held in Würzburg, Germany, in September 2019. The total of 130 regular papers presented in these volumes was carefully reviewed and selected from 733 submissions; there are 10 papers in the demo track. The contributions were organized in topical sections named as follows: Part I: pattern mining; clustering, anomaly and outlier detection, and autoencoders; dimensionality reduction and feature selection; social networks and graphs; decision trees, interpretability, and causality; strings and streams; privacy and security; optimization. Part II: supervised learning; multi-label learning; large-scale learning; deep learning; probabilistic models; natural language processing. Part III: reinforcement learning and bandits; ranking; applied data science: computer vision and explanation; applied data science: healthcare; applied data science: e-commerce, finance, and advertising; applied data science: rich data; applied data science: applications; demo track. Chapter "Heavy-tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Download or read book Approximation Randomization and Combinatorial Optimization Algorithms and Techniques written by Maria Serna and published by Springer Science & Business Media. This book was released on 2010-08-19 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the joint refereed proceedings of the 13th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2010, and the 14th International Workshop on Randomization and Computation, RANDOM 2010, held in Barcelona, Spain, in September 2010. The 28 revised full papers of the APPROX 2010 workshop and the 29 revised full papers of the RANDOM 2010 workshop included in this volume, were carefully reviewed and selected from 66 and 61 submissions, respectively. APPROX focuses on algorithmic and complexity issues surrounding the development of efficient approximate solutions to computationally difficult problems. RANDOM is concerned with applications of randomness to computational and combinatorial problems.
Download or read book Scalable Optimization via Probabilistic Modeling written by Martin Pelikan and published by Springer. This book was released on 2007-01-12 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: I’m not usually a fan of edited volumes. Too often they are an incoherent hodgepodge of remnants, renegades, or rejects foisted upon an unsuspecting reading public under a misleading or fraudulent title. The volume Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications is a worthy addition to your library because it succeeds on exactly those dimensions where so many edited volumes fail. For example, take the title, Scalable Optimization via Probabilistic M- eling: From Algorithms to Applications. You need not worry that you’re going to pick up this book and ?nd stray articles about anything else. This book focuseslikealaserbeamononeofthehottesttopicsinevolutionary compu- tion over the last decade or so: estimation of distribution algorithms (EDAs). EDAs borrow evolutionary computation’s population orientation and sel- tionism and throw out the genetics to give us a hybrid of substantial power, elegance, and extensibility. The article sequencing in most edited volumes is hard to understand, but from the get go the editors of this volume have assembled a set of articles sequenced in a logical fashion. The book moves from design to e?ciency enhancement and then concludes with relevant applications. The emphasis on e?ciency enhancement is particularly important, because the data-mining perspectiveimplicitinEDAsopensuptheworldofoptimizationtonewme- ods of data-guided adaptation that can further speed solutions through the construction and utilization of e?ective surrogates, hybrids, and parallel and temporal decompositions.
Download or read book Encyclopedia of Algorithms written by Ming-Yang Kao and published by Springer Science & Business Media. This book was released on 2008-08-06 with total page 1200 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of Springer’s renowned Major Reference Works, this awesome achievement provides a comprehensive set of solutions to important algorithmic problems for students and researchers interested in quickly locating useful information. This first edition of the reference focuses on high-impact solutions from the most recent decade, while later editions will widen the scope of the work. All entries have been written by experts, while links to Internet sites that outline their research work are provided. The entries have all been peer-reviewed. This defining reference is published both in print and on line.
Download or read book Design and Analysis of Algorithms written by Guy Even and published by Springer. This book was released on 2012-11-27 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First Mediterranean Conference on Algorithms, MedAlg 2012, held in Kibbutz Ein Gedi, Israel, in December 2012. The 18 papers presented were carefully reviewed and selected from 44 submissions. The conference papers focus on the design, engineering, theoretical and experimental performance analysis of algorithms for problems arising in different areas of computation. Topics covered include: communications networks, combinatorial optimization and approximation, parallel and distributed computing, computer systems and architecture, economics, game theory, social networks and the World Wide Web.
