@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"
}
@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|https://www.math.utah.edu/~beebe/|"}
@String{j-AMER-MATH-MONTHLY = "American Mathematical Monthly"}
@String{j-HIST-MATH = "Historia Mathematica"}
@String{j-SIAM-REVIEW = "SIAM Review"}
@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"}
@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"}
@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;
https://www.math.utah.edu/pub/tex/bib/master.bib;
https://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;
https://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;
https://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",
}
@Book{Brezinski:2023:JTH,
author = "Claude Brezinski and G{\'e}rard A. Meurant and Michela
{Redivo Zaglia}",
title = "A Journey Through the History of Numerical Linear
Algebra",
volume = "183",
publisher = pub-SIAM,
address = pub-SIAM:adr,
pages = "xix + 792",
year = "2023",
DOI = "https://doi.org/10.1137/1.9781611977233.fm",
ISBN = "1-61197-722-3 (hardcover), 1-61197-723-1 (e-book)",
ISBN-13 = "978-1-61197-722-6 (hardcover), 978-1-61197-723-3
(e-book)",
LCCN = "QA184.2",
MRclass = "01-02 01-08 65-03 68-03",
bibdate = "Mon Aug 7 08:38:41 MDT 2023",
bibsource = "fsz3950.oclc.org:210/WorldCat;
https://www.math.utah.edu/pub/tex/bib/master.bib;
https://www.math.utah.edu/pub/tex/bib/numana2020.bib",
series = "Other titles in applied mathematics",
abstract = "The book describes numerical methods proposed for
solving problems in linear algebra from antiquity to
the present. Focusing on methods for solving linear
systems of equations and eigenvalue problems, the book
also describes the interplay between numerical methods
and the computing tools available for solving these
problems. Biographies of the main contributors to the
field are included",
acknowledgement = ack-nhfb,
author-dates = "1941--",
libnote = "Not in my library.",
subject = "Algebras, Linear; History; Matrices; Numerical
calculations; Numerical analysis; Computer science ---
Historical",
tableofcontents = "Front Matter / i--xix \\
1: Matrices and their properties / 1--31 \\
2: Elimination methods for linear systems / 33--97 \\
3: Determinants / 99--119 \\
4: Matrix factorizations and canonical forms / 121--154
\\
5: Iterative methods for linear systems / 155--273 \\
6: Eigenvalues and eigenvectors / 275--322 \\
7: Computing machines / 323--355 \\
8: Software for numerical linear algebra / 357--380 \\
9: Miscellaneous topics / 381--399 \\
10: Lives and works / 401--604 \\
Back Matter / 605--793",
}
