High-Dimensional Indexing
High-Dimensional Indexing

Author: Cui Yu

Publisher: Springer

Published: 2003-08-01

Total Pages: 159

ISBN-13: 3540457704

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In this monograph, we study the problem of high-dimensional indexing and systematically introduce two efficient index structures: one for range queries and the other for similarity queries. Extensive experiments and comparison studies are conducted to demonstrate the superiority of the proposed indexing methods. Many new database applications, such as multimedia databases or stock price information systems, transform important features or properties of data objects into high-dimensional points. Searching for objects based on these features is thus a search of points in this feature space. To support efficient retrieval in such high-dimensional databases, indexes are required to prune the search space. Indexes for low-dimensional databases are well studied, whereas most of these application specific indexes are not scaleable with the number of dimensions, and they are not designed to support similarity searches and high-dimensional joins.

High-Dimensional Probability
High-Dimensional Probability

Author: Roman Vershynin

Publisher: Cambridge University Press

Published: 2018-09-27

Total Pages: 299

ISBN-13: 1108415199

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An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

High-Dimensional Data Analysis with Low-Dimensional Models
High-Dimensional Data Analysis with Low-Dimensional Models

Author: John Wright

Publisher: Cambridge University Press

Published: 2022-01-13

Total Pages: 718

ISBN-13: 1108805558

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Connecting theory with practice, this systematic and rigorous introduction covers the fundamental principles, algorithms and applications of key mathematical models for high-dimensional data analysis. Comprehensive in its approach, it provides unified coverage of many different low-dimensional models and analytical techniques, including sparse and low-rank models, and both convex and non-convex formulations. Readers will learn how to develop efficient and scalable algorithms for solving real-world problems, supported by numerous examples and exercises throughout, and how to use the computational tools learnt in several application contexts. Applications presented include scientific imaging, communication, face recognition, 3D vision, and deep networks for classification. With code available online, this is an ideal textbook for senior and graduate students in computer science, data science, and electrical engineering, as well as for those taking courses on sparsity, low-dimensional structures, and high-dimensional data. Foreword by Emmanuel Candès.

High-Dimensional Statistics
High-Dimensional Statistics

Author: Martin J. Wainwright

Publisher: Cambridge University Press

Published: 2019-02-21

Total Pages: 571

ISBN-13: 1108498027

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A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

New Directions in Statistical Physics
New Directions in Statistical Physics

Author: Luc T. Wille

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 369

ISBN-13: 3662089688

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This book provides a unique insight into the latest breakthroughs in a consistent manner, at a level accessible to undergraduates, yet with enough attention to the theory and computation to satisfy the professional researcher Statistical physics addresses the study and understanding of systems with many degrees of freedom. As such it has a rich and varied history, with applications to thermodynamics, magnetic phase transitions, and order/disorder transformations, to name just a few. However, the tools of statistical physics can be profitably used to investigate any system with a large number of components. Thus, recent years have seen these methods applied in many unexpected directions, three of which are the main focus of this volume. These applications have been remarkably successful and have enriched the financial, biological, and engineering literature. Although reported in the physics literature, the results tend to be scattered and the underlying unity of the field overlooked.

Database Theory - ICDT 2001
Database Theory - ICDT 2001

Author: Jan Van den Bussche

Publisher: Springer Science & Business Media

Published: 2001-02-08

Total Pages: 460

ISBN-13: 3540414568

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This book constitutes the refereed proceedings of the 8th International Conference on Database Theory, ICDT 2001, held in London, UK, in January 2001. The 26 revised full papers presented together with two invited papers were carefully reviewed and selected from 75 submissions. All current issues on database theory and the foundations of database systems are addressed. Among the topics covered are database queries, SQL, information retrieval, database logic, database mining, constraint databases, transactions, algorithmic aspects, semi-structured data, data engineering, XML, term rewriting, clustering, etc.

Big Data
Big Data

Author: Dan Olteanu

Publisher: Springer

Published: 2013-06-25

Total Pages: 312

ISBN-13: 3642394671

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This book constitutes the thoroughly refereed post-conference proceedings of the 29th British National Conference on Databases, BNCOD 2013, held in Oxford, UK, in July 2013. The 20 revised full papers, presented together with three keynote talks, two tutorials, and one panel session, were carefully reviewed and selected from 42 submissions. Special focus of the conference has been "Big Data" and so the papers cover a wide range of topics such as query and update processing; relational storage; benchmarking; XML query processing; big data; spatial data and indexing; data extraction and social networks.

Geometric Structure of High-Dimensional Data and Dimensionality Reduction
Geometric Structure of High-Dimensional Data and Dimensionality Reduction

Author: Jianzhong Wang

Publisher: Springer Science & Business Media

Published: 2012-04-28

Total Pages: 363

ISBN-13: 3642274978

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"Geometric Structure of High-Dimensional Data and Dimensionality Reduction" adopts data geometry as a framework to address various methods of dimensionality reduction. In addition to the introduction to well-known linear methods, the book moreover stresses the recently developed nonlinear methods and introduces the applications of dimensionality reduction in many areas, such as face recognition, image segmentation, data classification, data visualization, and hyperspectral imagery data analysis. Numerous tables and graphs are included to illustrate the ideas, effects, and shortcomings of the methods. MATLAB code of all dimensionality reduction algorithms is provided to aid the readers with the implementations on computers. The book will be useful for mathematicians, statisticians, computer scientists, and data analysts. It is also a valuable handbook for other practitioners who have a basic background in mathematics, statistics and/or computer algorithms, like internet search engine designers, physicists, geologists, electronic engineers, and economists. Jianzhong Wang is a Professor of Mathematics at Sam Houston State University, U.S.A.

Database Systems for Advanced Applications
Database Systems for Advanced Applications

Author: Hiroyuki Kitagawa

Publisher: Springer

Published: 2010-04-08

Total Pages: 515

ISBN-13: 3642120989

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This two volume set LNCS 5981 and LNCS 5982 constitutes the refereed proceedings of the 15th International Conference on Database Systems for Advanced Applications, DASFAA 2010, held in Tsukuba, Japan, in April 2010. The 39 revised full papers and 16 revised short papers presented together with 3 invited keynote papers, 22 demonstration papers, 6 industrial papers, and 2 keynote talks were carefully reviewed and selected from 285 submissions. The papers of the first volume are organized in topical sections on P2P-based technologies, data mining technologies, XML search and matching, graphs, spatial databases, XML technologies, time series and streams, advanced data mining, query processing, Web, sensor networks and communications, information management, as well as communities and Web graphs. The second volume contains contributions related to trajectories and moving objects, skyline queries, privacy and security, data streams, similarity search and event processing, storage and advanced topics, industrial, demo papers, and tutorials and panels.