%%% -*-BibTeX-*- %%% ==================================================================== %%% BibTeX-file{ %%% author = "Nelson H. F. Beebe", %%% version = "1.02", %%% date = "12 March 2022", %%% time = "09:14:06 MST", %%% filename = "numana2020.bib", %%% address = "University of Utah %%% Department of Mathematics, 110 LCB %%% 155 S 1400 E RM 233 %%% Salt Lake City, UT 84112-0090 %%% USA", %%% telephone = "+1 801 581 5254", %%% FAX = "+1 801 581 4148", %%% URL = "http://www.math.utah.edu/~beebe", %%% checksum = "08181 346 1595 16728", %%% email = "beebe at math.utah.edu, beebe at acm.org, %%% beebe at computer.org (Internet)", %%% codetable = "ISO/ASCII", %%% keywords = "bibliography; BibTeX; numerical analysis", %%% license = "public domain", %%% supported = "yes", %%% docstring = "This bibliography collects publications %%% in the large field of numerical analysis %%% from books and conference proceedings, but %%% excluding journal articles, which are covered %%% in separate bibliographies in the TeX User %%% Group archive. %%% %%% This file includes publications for the %%% decade 2020--2029. %%% %%% At version 1.02, the year coverage looked %%% like this: %%% %%% 2020 ( 2) 2021 ( 0) 2022 ( 1) %%% %%% Book: 3 %%% %%% Total entries: 3 %%% %%% In this bibliography, entries are sorted %%% first by ascending year, and within each %%% year, alphabetically by author or editor, %%% and then, if necessary, by the 3-letter %%% abbreviation at the end of the BibTeX %%% citation tag, using the bibsort -byyear %%% utility. Year order has been chosen to %%% make it easier to identify the most recent %%% work. %%% %%% The checksum field above contains a CRC-16 %%% checksum as the first value, followed by the %%% equivalent of the standard UNIX wc (word %%% count) utility output of lines, words, and %%% characters. This is produced by Robert %%% Solovay's checksum utility.", %%% } %%% ====================================================================

@Preamble{ "\ifx \undefined \booktitle \def \booktitle #1{{{\em #1}}} \fi" # "\ifx \undefined \k \let \k = \c \fi" # "\ifx \undefined \circled \def \circled #1{(#1)}\fi" # "\ifx \undefined \reg \def \reg {\circled{R}}\fi" }

%%%===================================================================== %%% Acknowledgement abbreviations:

@String{ack-nhfb= "Nelson H. F. Beebe, University of Utah, Department of Mathematics, 110 LCB, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090, USA, Tel: +1 801 581 5254, FAX: +1 801 581 4148, e-mail: \path|beebe@math.utah.edu|, \path|beebe@acm.org|, \path|beebe@computer.org| (Internet), URL: \path|http://www.math.utah.edu/~beebe/|"}

%%%===================================================================== %%% Journal abbreviations:

@String{j-AMER-MATH-MONTHLY= "American Mathematical Monthly"} @String{j-HIST-MATH= "Historia Mathematica"} @String{j-SIAM-REVIEW= "SIAM Review"}

%%%===================================================================== %%% Publishers and their addresses:

@String{pub-ACADEMIC= "Academic Press"} @String{pub-ACADEMIC:adr= "New York, NY, USA"} @String{pub-ACM= "ACM Press"} @String{pub-ACM:adr= "New York, NY 10036, USA"} @String{pub-AMS= "American Mathematical Society"} @String{pub-AMS:adr= "Providence, RI, USA"} @String{pub-BIRKHAUSER= "Birkh{\"{a}}user"} @String{pub-BIRKHAUSER:adr= "Cambridge, MA, USA; Berlin, Germany; Basel, Switzerland"} @String{pub-BIRKHAUSER-BOSTON= "Birkh{\"a}user Boston Inc."} @String{pub-BIRKHAUSER-BOSTON:adr= "Cambridge, MA, USA"} @String{pub-CAMBRIDGE= "Cambridge University Press"} @String{pub-CAMBRIDGE:adr= "Cambridge, UK"} @String{pub-CHAPMAN-HALL-CRC= "Chapman and Hall/CRC"} @String{pub-CHAPMAN-HALL-CRC:adr= "Boca Raton, FL, USA"} @String{pub-CLARENDON= "Clarendon Press"} @String{pub-CLARENDON:adr= "New York, NY, USA"} @String{pub-CRC= "CRC Press"} @String{pub-CRC:adr= "2000 N.W. Corporate Blvd., Boca Raton, FL 33431-9868, USA"} @String{pub-DOVER= "Dover"} @String{pub-DOVER:adr= "New York, NY, USA"} @String{pub-ELSEVIER-ACADEMIC= "Elsevier Academic Press"} @String{pub-ELSEVIER-ACADEMIC:adr= "Amsterdam, The Netherlands"} @String{pub-GRUYTER= "Walter de Gruyter"} @String{pub-GRUYTER:adr= "New York"} @String{pub-JOHNS-HOPKINS= "The Johns Hopkins University Press"} @String{pub-JOHNS-HOPKINS:adr= "Baltimore, MD, USA"} @String{pub-KNOPF= "Alfred A. Knopf"} @String{pub-KNOPF:adr= "New York, NY, USA"} @String{pub-OLDENBOURG= "R. Oldenbourg"} @String{pub-OLDENBOURG:adr= "M{\"u}nchen, Germany"} @String{pub-OXFORD= "Oxford University Press"} @String{pub-OXFORD:adr= "Walton Street, Oxford OX2 6DP, UK"} @String{pub-PACKT= "Packt Publishing"} @String{pub-PACKT:adr= "Birmingham, UK"} @String{pub-PH= "Pren{\-}tice-Hall"} @String{pub-PH:adr= "Upper Saddle River, NJ 07458, USA"} @String{pub-PRINCETON= "Princeton University Press"} @String{pub-PRINCETON:adr= "Princeton, NJ, USA"} @String{pub-SIAM= "Society for Industrial and Applied Mathematics"} @String{pub-SIAM:adr= "Philadelphia, PA, USA"} @String{pub-SV= "Springer-Verlag"} @String{pub-SV:adr= "Berlin, Germany~/ Heidelberg, Germany~/ London, UK~/ etc."} @String{pub-WILEY= "Wiley"} @String{pub-WILEY:adr= "New York, NY, USA"} @String{pub-WORLD-SCI= "World Scientific Publishing Co."} @String{pub-WORLD-SCI:adr= "Singapore; Philadelphia, PA, USA; River Edge, NJ, USA"}

%%% ==================================================================== %%% Series abbreviations:

@String{ser-LECT-NOTES-MATH= "Lecture Notes in Mathematics"} @String{ser-LNAI= "Lecture Notes in Artificial Intelligence"} @String{ser-LNCS= "Lecture Notes in Computer Science"} @String{ser-LNCSE= "Lecture Notes in Computational Science and Engineering"}

%%%===================================================================== %%% Bibliography entries, sorted by year, and then by citation label, %%% with `bibsort -byyear':

@Book{Blum:2020:FDS, author = "Avrim Blum and John Hopcroft and Ravi Kannan", title = "Foundations of Data Science", publisher = pub-CAMBRIDGE, address = pub-CAMBRIDGE:adr, pages = "viii + 424", year = "2020", ISBN = "1-108-48506-5 (hardcover), 1-108-75552-6 (e-book)", ISBN-13 = "978-1-108-48506-7 (hardcover), 978-1-108-75552-8 (e-book)", LCCN = "QA76 .B5675 2020", bibdate = "Tue Mar 17 08:01:49 MDT 2020", bibsource = "fsz3950.oclc.org:210/WorldCat; http://www.math.utah.edu/pub/tex/bib/master.bib; http://www.math.utah.edu/pub/tex/bib/numana2020.bib", abstract = "This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.", acknowledgement = ack-nhfb, libnote = "Not in my library.", } @Book{Pence:2020:EMEd, author = "T. J. (Thomas J.) Pence and I. S. (Indrek S.) Wichman", title = "Essential Mathematics for Engineers and Scientists", publisher = pub-CAMBRIDGE, address = pub-CAMBRIDGE:adr, pages = "xix + 736", year = "2020", ISBN = "1-108-67135-7", ISBN-13 = "978-1-108-42544-5 (hardcover), 978-1-108-67135-4 (e-book)", LCCN = "QA37.3 .P46 2020", bibdate = "Mon Aug 31 07:04:32 MDT 2020", bibsource = "fsz3950.oclc.org:210/WorldCat; http://www.math.utah.edu/pub/tex/bib/numana2020.bib", abstract = "This text is geared toward students who have an undergraduate degree or extensive coursework in engineering or the physical sciences and who wish to develop their understanding of the essential topics of applied mathematics. The methods covered in the chapters form the core of analysis in engineering and the physical sciences. Readers will learn the solutions, techniques, and approaches that they will use as academic researchers or industrial R and D specialists. For example, they will be able to understand the fundamentals behind the various scientific software packages that are used to solve technical problems (such as the equations describing the solid mechanics of complex structures or the fluid mechanics of short-term weather prediction and long-term climate change), which is crucial to working with such codes successfully. Detailed and numerous worked problems help to ensure a clear and well-paced introduction to applied mathematics. Computational challenge problems at the end of each chapter provide students with the opportunity for hands-on learning and help to ensure mastery of the concepts. Adaptable to one- and two-semester courses.", acknowledgement = ack-nhfb, subject = "Mathematics; Mathematical analysis; Engineering mathematics; Science; Engineering mathematics.; Mathematical analysis.; Mathematics.", tableofcontents = "Linear algebra and finite dimensional vector spaces \\ Linear transformations \\ Application to systems of equations \\ The spectrum of eigenvalues \\ Complex variables: basic concepts \\ Analytic functions of a complex variable \\ The Cauchy integral theorems \\ Series expansions and contour integration \\ Linear partial differential equations \\ Linear ordinary differential equations \\ Green's functions for ordinary differential equations \\ Poisson's equation and Green's functions \\ Combined Green's function and eigenfunction methods", } @Book{Allahviranloo:2022:ANA, author = "Tofigh Allahviranloo and Witold Pedrycz and Armin Esfandiari", title = "Advances in Numerical Analysis Emphasizing Interval Data", publisher = pub-CRC, address = pub-CRC:adr, pages = "224 (est.)", year = "2022", ISBN = "1-00-054025-1 (e-book), 1-00-054031-6 (ePUB), 1-00-321817-2 (e-book), 1-03-211043-0 (hardcover)", ISBN-13 = "978-1-00-054025-3 (e-book), 978-1-00-054031-4 (ePUB), 978-1-00-321817-3 (e-book), 978-1-03-211043-1 (hardcover)", LCCN = "QA297 .A55 2022", bibdate = "Sat Mar 12 09:06:25 MST 2022", bibsource = "fsz3950.oclc.org:210/WorldCat; http://www.math.utah.edu/pub/tex/bib/numana2020.bib", abstract = "Numerical analysis forms a cornerstone of numeric computing and optimization, in particular recently, interval numerical computations play an important role in these topics. The interest of researchers in computations involving uncertain data, namely interval data opens new avenues in coping with real-world problems and deliver innovative and efficient solutions. This book provides the basic theoretical foundations of numerical methods, discusses key technique classes, explains improvements and improvements, and provides insights into recent developments and challenges. The theoretical parts of numerical methods, including the concept of interval approximation theory, are introduced and explained in detail. In general, the key features of the book include an up-to-date and focused treatise on error analysis in calculations, in particular the comprehensive and systematic treatment of error propagation mechanisms, considerations on the quality of data involved in numerical calculations, and a thorough discussion of interval approximation theory. Moreover, this book focuses on approximation theory and its development from the perspective of linear algebra, and new and regular representations of numerical integration and their solutions are enhanced by error analysis as well. The book is unique in the sense that its content and organization will cater to several audiences, in particular graduate students, researchers, and practitioners.", acknowledgement = ack-nhfb, subject = "Numerical analysis; Technology; Electricity", tableofcontents = "1. Introduction \\ 2. Error analysis \\ 3. Interpolation \\ 4. Advanced interpolation \\ 5. Interval Interpolation \\ 6. Interpolation from the Linear Algebra Point of View \\ 7. Newton-Cotes Quadrature \\ 8. Interval Newton-Cotes Quadrature \\ 9. Gauss Integration", }