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A Ramble Through Probability: How I Learned to Stop Worrying and Love Measure Theory
https://epubs.siam.org/doi/book/10.1137/1.9781611977820?mi=ab3l03&af=R&pubType=book&target=browse
A Ramble Through Probability: How I Learned to Stop Worrying and Love Measure Theory. <br/> Measure theory and probability are fascinating subjects, with proofs that describe profound ways to reason, leading to results that are frequently startling, beautiful, and useful. Measure theory and probability also played colorful roles in the development of pure and applied mathematics, statistics, engineering, physics, and finance. Indeed, it would be very difficult to overstate the central importance of measure theory and probability in the quantitative disciplines. This book is intended to provide a widely accessible introduction to these subjects.
A Ramble Through Probability: How I Learned to Stop Worrying and Love Measure Theory. <br/> Measure theory and probability are fascinating subjects, with proofs that describe profound ways to reason, leading to results that are frequently startling, beautiful, and useful. Measure theory and probability also played colorful roles in the development of pure and applied mathematics, statistics, engineering, physics, and finance. Indeed, it would be very difficult to overstate the central importance of measure theory and probability in the quantitative disciplines. This book is intended to provide a widely accessible introduction to these subjects.
A Ramble Through Probability: How I Learned to Stop Worrying and Love Measure Theory
doi:10.1137/1.9781611977820
Samopriya Basu
Troy Butler
Don Estep
Nishant Panda
A Ramble Through Probability: How I Learned to Stop Worrying and Love Measure Theory
20240206T06:26:07Z
10.1137/1.9781611977820
https://epubs.siam.org/doi/book/10.1137/1.9781611977820?mi=ab3l03&af=R&pubType=book&target=browse
© 2024 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Error Norm Estimation in the Conjugate Gradient Algorithm
https://epubs.siam.org/doi/book/10.1137/1.9781611977868?mi=ab3l03&af=R&pubType=book&target=browse
Error Norm Estimation in the Conjugate Gradient Algorithm. <br/> Today the conjugate gradient (CG) algorithm is almost always the iterative method of choice for solving linear systems with symmetric positive definite matrices. It was developed independently by M. R. Hestenes in the United States and E. L. Stiefel in Switzerland at the beginning of the 1950s. After a visit of Stiefel in 1951 to the Institute of Numerical Analysis (INA), located on the campus of the University of California at Los Angeles where Hestenes was working, they wrote a joint paper [50] which was published in the December 1952 issue of the Journal of the National Bureau of Standards. For the early history of CG, we refer the reader to [8] and the references therein as well as to [38, 79, 80].
Error Norm Estimation in the Conjugate Gradient Algorithm. <br/> Today the conjugate gradient (CG) algorithm is almost always the iterative method of choice for solving linear systems with symmetric positive definite matrices. It was developed independently by M. R. Hestenes in the United States and E. L. Stiefel in Switzerland at the beginning of the 1950s. After a visit of Stiefel in 1951 to the Institute of Numerical Analysis (INA), located on the campus of the University of California at Los Angeles where Hestenes was working, they wrote a joint paper [50] which was published in the December 1952 issue of the Journal of the National Bureau of Standards. For the early history of CG, we refer the reader to [8] and the references therein as well as to [38, 79, 80].
Error Norm Estimation in the Conjugate Gradient Algorithm
doi:10.1137/1.9781611977868
Gérard Meurant
Petr Tichý
Error Norm Estimation in the Conjugate Gradient Algorithm
20240130T06:19:15Z
10.1137/1.9781611977868
https://epubs.siam.org/doi/book/10.1137/1.9781611977868?mi=ab3l03&af=R&pubType=book&target=browse
© 2024 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Algorithmic Mathematics in Machine Learning
https://epubs.siam.org/doi/book/10.1137/1.9781611977882?mi=ab3l03&af=R&pubType=book&target=browse
Algorithmic Mathematics in Machine Learning. <br/> The story of machine learning is one of rigorous success. It is frequently employed by scientists and practitioners around the globe in various areas of application ranging from economics to chemistry, from medicine to engineering, from gaming to astronomy, and from speech processing to computer vision. While the remarkable success of machine learning methods speaks for itself, they are often applied in an ad hoc manner without much care for their mathematical foundation or for their algorithmic intricacies. Therefore, we decided to write this book. Our goal is to provide the necessary background on commonly used machine learning algorithms and to highlight important implementational and numerical details. The book is based on a wellreceived practical lab course, which we established within the mathematics studies course at the University of Bonn, Germany, in 2017. The course has been taught and successively enhanced each year since then.
Algorithmic Mathematics in Machine Learning. <br/> The story of machine learning is one of rigorous success. It is frequently employed by scientists and practitioners around the globe in various areas of application ranging from economics to chemistry, from medicine to engineering, from gaming to astronomy, and from speech processing to computer vision. While the remarkable success of machine learning methods speaks for itself, they are often applied in an ad hoc manner without much care for their mathematical foundation or for their algorithmic intricacies. Therefore, we decided to write this book. Our goal is to provide the necessary background on commonly used machine learning algorithms and to highlight important implementational and numerical details. The book is based on a wellreceived practical lab course, which we established within the mathematics studies course at the University of Bonn, Germany, in 2017. The course has been taught and successively enhanced each year since then.
Algorithmic Mathematics in Machine Learning
doi:10.1137/1.9781611977882
Bastian Bohn
Jochen Garcke
Michael Griebel
Algorithmic Mathematics in Machine Learning
20240325T09:13:41Z
10.1137/1.9781611977882
https://epubs.siam.org/doi/book/10.1137/1.9781611977882?mi=ab3l03&af=R&pubType=book&target=browse
© 2024 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Machine Learning for Asset Management and Pricing
https://epubs.siam.org/doi/book/10.1137/1.9781611977905?mi=ab3l03&af=R&pubType=book&target=browse
Machine Learning for Asset Management and Pricing. <br/> This textbook covers various machine learning methods applied to asset and liability management, as well as asset pricing. We shortened the title to Machine Learning for Asset Management and Pricing for practical reasons, but also more fundamental ones. First, we do not give much space to liabilities in this book. It would not render justice to the field of asset and liability management (ALM) to include liabilities in the title. It is, however, important for a student to realize that the comprehensive problem of ALM can be handled (at least in theory) using the same theories and methods as asset management or liability management.
Machine Learning for Asset Management and Pricing. <br/> This textbook covers various machine learning methods applied to asset and liability management, as well as asset pricing. We shortened the title to Machine Learning for Asset Management and Pricing for practical reasons, but also more fundamental ones. First, we do not give much space to liabilities in this book. It would not render justice to the field of asset and liability management (ALM) to include liabilities in the title. It is, however, important for a student to realize that the comprehensive problem of ALM can be handled (at least in theory) using the same theories and methods as asset management or liability management.
Machine Learning for Asset Management and Pricing
doi:10.1137/1.9781611977905
Henry Schellhorn
Tianmin Kong
Machine Learning for Asset Management and Pricing
20240305T10:32:55Z
10.1137/1.9781611977905
https://epubs.siam.org/doi/book/10.1137/1.9781611977905?mi=ab3l03&af=R&pubType=book&target=browse
© 2024 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Numerical Methods for Least Squares Problems: Second Edition
https://epubs.siam.org/doi/book/10.1137/1.9781611977950?mi=ab3l03&af=R&pubType=book&target=browse
Numerical Methods for Least Squares Problems: Second Edition. <br/> Excerpt
Numerical Methods for Least Squares Problems: Second Edition. <br/> Excerpt
Numerical Methods for Least Squares Problems: Second Edition
doi:10.1137/1.9781611977950
Åke Björck
Numerical Methods for Least Squares Problems: Second Edition
20240409T02:33:49Z
10.1137/1.9781611977950
https://epubs.siam.org/doi/book/10.1137/1.9781611977950?mi=ab3l03&af=R&pubType=book&target=browse
© 2024 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

SetValued, Convex, and Nonsmooth Analysis in Dynamics and Control: An Introduction
https://epubs.siam.org/doi/book/10.1137/1.9781611977981?mi=ab3l03&af=R&pubType=book&target=browse
SetValued, Convex, and Nonsmooth Analysis in Dynamics and Control: An Introduction. <br/> Excerpt
SetValued, Convex, and Nonsmooth Analysis in Dynamics and Control: An Introduction. <br/> Excerpt
SetValued, Convex, and Nonsmooth Analysis in Dynamics and Control: An Introduction
doi:10.1137/1.9781611977981
Rafal K. Goebel
SetValued, Convex, and Nonsmooth Analysis in Dynamics and Control: An Introduction
20240409T02:34:19Z
10.1137/1.9781611977981
https://epubs.siam.org/doi/book/10.1137/1.9781611977981?mi=ab3l03&af=R&pubType=book&target=browse
© 2024 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Dynamics and Bifurcation in Networks: Theory and Applications of Coupled Differential Equations
https://epubs.siam.org/doi/book/10.1137/1.9781611977332?mi=ab3l03&af=R&pubType=book&target=browse
Dynamics and Bifurcation in Networks: Theory and Applications of Coupled Differential Equations. <br/> The biologist J. B. S. Haldane, when asked what we can learn about the Creator by examining the world, is said to have replied “an inordinate fondness for beetles” [705]. Today's biologists could be forgiven for pointing to an inordinate fondness for networks. Networks are ubiquitous in the life sciences: examples include genetic regulatory networks, neural circuitry, ecological food webs, phylogenetic trees, and epidemic networks. Networks are also common in many other branches of science, including physics, chemistry, computer science, electrical and electronic engineering, psychology, and sociology. In recent years there has been an explosion of interest in networkbased modeling, and the research literature, including both theory and applications, now extends to many thousands of papers. The questions addressed and the techniques involved are extremely diverse, reflecting the broad range of backgrounds and interests of researchers.
Dynamics and Bifurcation in Networks: Theory and Applications of Coupled Differential Equations. <br/> The biologist J. B. S. Haldane, when asked what we can learn about the Creator by examining the world, is said to have replied “an inordinate fondness for beetles” [705]. Today's biologists could be forgiven for pointing to an inordinate fondness for networks. Networks are ubiquitous in the life sciences: examples include genetic regulatory networks, neural circuitry, ecological food webs, phylogenetic trees, and epidemic networks. Networks are also common in many other branches of science, including physics, chemistry, computer science, electrical and electronic engineering, psychology, and sociology. In recent years there has been an explosion of interest in networkbased modeling, and the research literature, including both theory and applications, now extends to many thousands of papers. The questions addressed and the techniques involved are extremely diverse, reflecting the broad range of backgrounds and interests of researchers.
Dynamics and Bifurcation in Networks: Theory and Applications of Coupled Differential Equations
doi:10.1137/1.9781611977332
Martin Golubitsky
Ian Stewart
Dynamics and Bifurcation in Networks: Theory and Applications of Coupled Differential Equations
20230424T01:34:47Z
10.1137/1.9781611977332
https://epubs.siam.org/doi/book/10.1137/1.9781611977332?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Matrix Analysis and Applied Linear Algebra, Second Edition
https://epubs.siam.org/doi/book/10.1137/1.9781611977448?mi=ab3l03&af=R&pubType=book&target=browse
Matrix Analysis and Applied Linear Algebra, Second Edition. <br/> This second edition of Matrix Analysis and Applied Linear Algebra differs substantially from the first edition in that this edition has been completely rewritten to include reformulations, extensions, and pedagogical enhancements. The goal in preparing this edition was to create an easily readable and flexible textbook that is adaptable for a single semester course or a more complete twosemester course. The following features are some of the characteristics of this edition.
Matrix Analysis and Applied Linear Algebra, Second Edition. <br/> This second edition of Matrix Analysis and Applied Linear Algebra differs substantially from the first edition in that this edition has been completely rewritten to include reformulations, extensions, and pedagogical enhancements. The goal in preparing this edition was to create an easily readable and flexible textbook that is adaptable for a single semester course or a more complete twosemester course. The following features are some of the characteristics of this edition.
Matrix Analysis and Applied Linear Algebra, Second Edition
doi:10.1137/1.9781611977448
Carl D. Meyer
Matrix Analysis and Applied Linear Algebra, Second Edition
20230629T08:32:40Z
10.1137/1.9781611977448
https://epubs.siam.org/doi/book/10.1137/1.9781611977448?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Matrix Analysis and Applied Linear Algebra, Second Edition: Study and Solutions Guide
https://epubs.siam.org/doi/book/10.1137/1.9781611977462?mi=ab3l03&af=R&pubType=book&target=browse
Matrix Analysis and Applied Linear Algebra, Second Edition: Study and Solutions Guide. <br/>
Matrix Analysis and Applied Linear Algebra, Second Edition: Study and Solutions Guide. <br/>
Matrix Analysis and Applied Linear Algebra, Second Edition: Study and Solutions Guide
doi:10.1137/1.9781611977462
Carl D. Meyer
Matrix Analysis and Applied Linear Algebra, Second Edition: Study and Solutions Guide
20230629T08:34:40Z
10.1137/1.9781611977462
https://epubs.siam.org/doi/book/10.1137/1.9781611977462?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Computational Discovery on Jupyter
https://epubs.siam.org/doi/book/10.1137/1.9781611977509?mi=ab3l03&af=R&pubType=book&target=browse
Computational Discovery on Jupyter. <br/>This is a different sort of book (indeed, we're a bit doubtful about calling it a “book,” even), intended for a different sort of course. The content is intended to be outside the normal mathematics curriculum. The book won't teach calculus or linear algebra, for example, although it will reinforce, support, and illuminate those subjects, which we imagine you will be taking eventually (possibly even concurrently). We assume only high school mathematics to start, although we get pretty deep pretty quickly. What does this mean? We assume that you have been exposed to algebra, matrices, functions, and basic calculus (informal limits, continuity, some rules for taking derivatives and antiderivatives). We assume no prior programming knowledge. We assume you've met with mathematical induction. What we mostly assume is that you're willing to take charge of your own learning. You should be prepared to actually do things as you read. There are activities to do, ranging from simple (with reports on what we did in the Reports section so you have more models of the process) to hard, namely projects that can be done by teams (and if you answer them, you could contribute a chapter to this book, maybe), and some actually open. If you answer one of those, you should publish a paper in a journal. Maple Transactions1 might be a good place.
Computational Discovery on Jupyter. <br/>This is a different sort of book (indeed, we're a bit doubtful about calling it a “book,” even), intended for a different sort of course. The content is intended to be outside the normal mathematics curriculum. The book won't teach calculus or linear algebra, for example, although it will reinforce, support, and illuminate those subjects, which we imagine you will be taking eventually (possibly even concurrently). We assume only high school mathematics to start, although we get pretty deep pretty quickly. What does this mean? We assume that you have been exposed to algebra, matrices, functions, and basic calculus (informal limits, continuity, some rules for taking derivatives and antiderivatives). We assume no prior programming knowledge. We assume you've met with mathematical induction. What we mostly assume is that you're willing to take charge of your own learning. You should be prepared to actually do things as you read. There are activities to do, ranging from simple (with reports on what we did in the Reports section so you have more models of the process) to hard, namely projects that can be done by teams (and if you answer them, you could contribute a chapter to this book, maybe), and some actually open. If you answer one of those, you should publish a paper in a journal. Maple Transactions1 might be a good place.
Computational Discovery on Jupyter
doi:10.1137/1.9781611977509
Neil J. Calkin
Eunice Y. S. Chan
Robert M. Corless
Computational Discovery on Jupyter
20231107T07:45:38Z
10.1137/1.9781611977509
https://epubs.siam.org/doi/book/10.1137/1.9781611977509?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Rounding Errors in Algebraic Processes
https://epubs.siam.org/doi/book/10.1137/1.9781611977523?mi=ab3l03&af=R&pubType=book&target=browse
Rounding Errors in Algebraic Processes. <br/> The development of automatic digital computers has made it possible to carry out computations involving a very large number of arithmetic operations and this has stimulated a study of the cumulative effect of rounding errors. In this book I have given an elementary introduction to this subject which is based on the work which has been done in the Mathematics Division of N.P.L. in the past few years. Some of the material presented here has already appeared in published papers, but much of it has hitherto been available only in the form of rough notes for lectures given in this country and the United States.
Rounding Errors in Algebraic Processes. <br/> The development of automatic digital computers has made it possible to carry out computations involving a very large number of arithmetic operations and this has stimulated a study of the cumulative effect of rounding errors. In this book I have given an elementary introduction to this subject which is based on the work which has been done in the Mathematics Division of N.P.L. in the past few years. Some of the material presented here has already appeared in published papers, but much of it has hitherto been available only in the form of rough notes for lectures given in this country and the United States.
Rounding Errors in Algebraic Processes
doi:10.1137/1.9781611977523
James Hardy Wilkinson
Rounding Errors in Algebraic Processes
20230613T03:31:17Z
10.1137/1.9781611977523
https://epubs.siam.org/doi/book/10.1137/1.9781611977523?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Network Information Systems: A Dynamical Systems Approach
https://epubs.siam.org/doi/book/10.1137/1.9781611977547?mi=ab3l03&af=R&pubType=book&target=browse
Network Information Systems: A Dynamical Systems Approach. <br/> Recent technological advances in communications and computation have spurred a broad interest in control of networks and control over networks. Network systems involve distributed decisionmaking for coordination of networks of dynamic agents and address a broad area of applications, including cooperative control of unmanned air vehicles, microsatellite clusters, mobile robotics, battle space management, congestion control in communication networks, intelligent vehicle/highway systems, largescale manufacturing systems, and biological networks, to cite but a few examples. To address the problem of autonomy and complexity for control and coordination of network systems, in this monograph we look to system thermodynamics and dynamical systems theory for inspiration in developing innovative architectures for controlling network systems.
Network Information Systems: A Dynamical Systems Approach. <br/> Recent technological advances in communications and computation have spurred a broad interest in control of networks and control over networks. Network systems involve distributed decisionmaking for coordination of networks of dynamic agents and address a broad area of applications, including cooperative control of unmanned air vehicles, microsatellite clusters, mobile robotics, battle space management, congestion control in communication networks, intelligent vehicle/highway systems, largescale manufacturing systems, and biological networks, to cite but a few examples. To address the problem of autonomy and complexity for control and coordination of network systems, in this monograph we look to system thermodynamics and dynamical systems theory for inspiration in developing innovative architectures for controlling network systems.
Network Information Systems: A Dynamical Systems Approach
doi:10.1137/1.9781611977547
Wassim M. Haddad
Qing Hui
Junsoo Lee
Network Information Systems: A Dynamical Systems Approach
20230622T07:10:38Z
10.1137/1.9781611977547
https://epubs.siam.org/doi/book/10.1137/1.9781611977547?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Moment and Polynomial Optimization
https://epubs.siam.org/doi/book/10.1137/1.9781611977608?mi=ab3l03&af=R&pubType=book&target=browse
Moment and Polynomial Optimization. <br/> Moment and polynomial optimization has received high attention in recent decades. It has beautiful theory and efficient methods, as well as broad applications for various mathematical, scientific, and engineering fields. The research status of optimization has been enhanced extensively due to its recent developments. Nowadays, moment and polynomial optimization is an important technique in many fields.
Moment and Polynomial Optimization. <br/> Moment and polynomial optimization has received high attention in recent decades. It has beautiful theory and efficient methods, as well as broad applications for various mathematical, scientific, and engineering fields. The research status of optimization has been enhanced extensively due to its recent developments. Nowadays, moment and polynomial optimization is an important technique in many fields.
Moment and Polynomial Optimization
doi:10.1137/1.9781611977608
Jiawang Nie
Moment and Polynomial Optimization
20230622T07:07:58Z
10.1137/1.9781611977608
https://epubs.siam.org/doi/book/10.1137/1.9781611977608?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied Mathematics

Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, Second Edition
https://epubs.siam.org/doi/book/10.1137/1.9781611977622?mi=ab3l03&af=R&pubType=book&target=browse
Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, Second Edition. <br/> Preface to the Second Edition: The second edition features two significant enhancements to the first edition. 1. Python codes were added on top of the existing MATLAB codes to illustrate and demonstrate different aspects of the algorithmic and applicative nature of nonlinear optimization. Since the first edition's publication, Python has become one of the leading software languages for scientific computing and is used in many applications, most notably those arising in data science. Readers interested in implementation may choose to follow either the MATLAB or Python codes which appear, sometimes literally, side by side. A new section on the Python module CVXPY (Section 8.5) describes how to solve convex optimization problems using Python.
Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, Second Edition. <br/> Preface to the Second Edition: The second edition features two significant enhancements to the first edition. 1. Python codes were added on top of the existing MATLAB codes to illustrate and demonstrate different aspects of the algorithmic and applicative nature of nonlinear optimization. Since the first edition's publication, Python has become one of the leading software languages for scientific computing and is used in many applications, most notably those arising in data science. Readers interested in implementation may choose to follow either the MATLAB or Python codes which appear, sometimes literally, side by side. A new section on the Python module CVXPY (Section 8.5) describes how to solve convex optimization problems using Python.
Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, Second Edition
doi:10.1137/1.9781611977622
Amir Beck
Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, Second Edition
20230629T08:36:40Z
10.1137/1.9781611977622
https://epubs.siam.org/doi/book/10.1137/1.9781611977622?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied Mathematics

A First Course in Options Pricing Theory
https://epubs.siam.org/doi/book/10.1137/1.9781611977646?mi=ab3l03&af=R&pubType=book&target=browse
A First Course in Options Pricing Theory. <br/> Financial derivatives, such as stock options for instance, are indispensable instruments in modern financial markets. The introduction of options markets in the early 1970s, and the continuous appearance of new types of complex derivative contracts, resulted in a rapid growth of interest in the theoretical aspects of options valuation. Since its inception in 1900 by the French mathematician Bachelier, options pricing theory has evolved into a modern discipline with a vast literature and dedicated university courses. While still considered in large part an advanced topic, it has become more and more common to find courses on options pricing theory in the undergraduate program of major universities all around the world. Moreover, financial institutions have since long recognized the pivotal role of mathematical models for their proper functionality and consistently offer employment opportunities for mathematicians.
A First Course in Options Pricing Theory. <br/> Financial derivatives, such as stock options for instance, are indispensable instruments in modern financial markets. The introduction of options markets in the early 1970s, and the continuous appearance of new types of complex derivative contracts, resulted in a rapid growth of interest in the theoretical aspects of options valuation. Since its inception in 1900 by the French mathematician Bachelier, options pricing theory has evolved into a modern discipline with a vast literature and dedicated university courses. While still considered in large part an advanced topic, it has become more and more common to find courses on options pricing theory in the undergraduate program of major universities all around the world. Moreover, financial institutions have since long recognized the pivotal role of mathematical models for their proper functionality and consistently offer employment opportunities for mathematicians.
A First Course in Options Pricing Theory
doi:10.1137/1.9781611977646
Simone Calogero
A First Course in Options Pricing Theory
20230629T08:35:20Z
10.1137/1.9781611977646
https://epubs.siam.org/doi/book/10.1137/1.9781611977646?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Classical Analysis of RealValued Functions
https://epubs.siam.org/doi/book/10.1137/1.9781611977677?mi=ab3l03&af=R&pubType=book&target=browse
Classical Analysis of RealValued Functions. <br/>The classical analysis of realvalued functions of one or more variables includes (along with other disciplines) elementary number theory, sequences and series, continuity and differentiability, proper and improper Riemann (RiemannStieltjes) integrals, elementary functions, investigation of graphs, implicit functions and dependence, uniform convergence, and integrals depending on a parameter. This book contains all these subjects and combines them based on a unified approach, starting with the theory of real numbers. In addition it contains Lebesgue measure and Lebesgue integration. The approach here is similar to Jordan measure and corresponding Riemann integration. Usually this material is not included in university courses for first and secondyear students, but we include it in this book on classical analysis due to the importance of Lebesgue's ideas and their connections with classical analysis.
Classical Analysis of RealValued Functions. <br/>The classical analysis of realvalued functions of one or more variables includes (along with other disciplines) elementary number theory, sequences and series, continuity and differentiability, proper and improper Riemann (RiemannStieltjes) integrals, elementary functions, investigation of graphs, implicit functions and dependence, uniform convergence, and integrals depending on a parameter. This book contains all these subjects and combines them based on a unified approach, starting with the theory of real numbers. In addition it contains Lebesgue measure and Lebesgue integration. The approach here is similar to Jordan measure and corresponding Riemann integration. Usually this material is not included in university courses for first and secondyear students, but we include it in this book on classical analysis due to the importance of Lebesgue's ideas and their connections with classical analysis.
Classical Analysis of RealValued Functions
doi:10.1137/1.9781611977677
Classical Analysis of RealValued Functions
20230915T07:22:53Z
10.1137/1.9781611977677
https://epubs.siam.org/doi/book/10.1137/1.9781611977677?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Calculus for the Natural Sciences
https://epubs.siam.org/doi/book/10.1137/1.9781611977691?mi=ab3l03&af=R&pubType=book&target=browse
Calculus for the Natural Sciences. <br/>This textbook is intended for a twosemester course on calculus of one variable. The target audience is comprised of students in biology, chemistry, mathematics, physics, and related disciplines, as well as professionals in these areas. It grew out of the Symbiosis Project at East Tennessee State University.
Calculus for the Natural Sciences. <br/>This textbook is intended for a twosemester course on calculus of one variable. The target audience is comprised of students in biology, chemistry, mathematics, physics, and related disciplines, as well as professionals in these areas. It grew out of the Symbiosis Project at East Tennessee State University.
Calculus for the Natural Sciences
doi:10.1137/1.9781611977691
Calculus for the Natural Sciences
20230913T03:50:17Z
10.1137/1.9781611977691
https://epubs.siam.org/doi/book/10.1137/1.9781611977691?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Mathematical Theory of Finite Elements
https://epubs.siam.org/doi/book/10.1137/1.9781611977738?mi=ab3l03&af=R&pubType=book&target=browse
Mathematical Theory of Finite Elements. <br/> This monograph is based on my personal lecture notes for the graduate course on Mathematical Theory of Finite Elements (EM394H) that I have been teaching at ICES (now the Oden Institute), at the University of Texas at Austin, since 2005. The class has been offered in two versions. The first version is devoted to a study of the energy spaces corresponding to the exact gradcurldiv sequence. The class is rather involved mathematically, and I taught it only every three or four years; see [27] for the corresponding lecture notes. The second, more popular version is covered in the presented notes.
Mathematical Theory of Finite Elements. <br/> This monograph is based on my personal lecture notes for the graduate course on Mathematical Theory of Finite Elements (EM394H) that I have been teaching at ICES (now the Oden Institute), at the University of Texas at Austin, since 2005. The class has been offered in two versions. The first version is devoted to a study of the energy spaces corresponding to the exact gradcurldiv sequence. The class is rather involved mathematically, and I taught it only every three or four years; see [27] for the corresponding lecture notes. The second, more popular version is covered in the presented notes.
Mathematical Theory of Finite Elements
doi:10.1137/1.9781611977738
Leszek F. Demkowicz
Mathematical Theory of Finite Elements
20230927T07:29:04Z
10.1137/1.9781611977738
https://epubs.siam.org/doi/book/10.1137/1.9781611977738?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization
https://epubs.siam.org/doi/book/10.1137/1.9781611977769?mi=ab3l03&af=R&pubType=book&target=browse
Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization. <br/> The authors of this book wanted for a long time to have at hand a large number of problems with solutions while teaching. The first author has taught IE303 Modeling and Methods in Optimization for Bilkent University students for longer than 20 years. A graduate student (a PhD candidate) assistant joined next and started compiling solved problems to be used in exams, quizzes, and homework assignments. The first author added some problems of his own. The result is this book. There are not many books out there dedicated to problems in integer optimization and related topics. The book focuses on the topics covered in IE303 Modeling and Methods in Optimization, a third year required course for Industrial Engineering students at Bilkent University. However, it should be useful for any undergraduate student in industrial engineering or in related disciplines. These are the motivations behind the preparation of this book.
Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization. <br/> The authors of this book wanted for a long time to have at hand a large number of problems with solutions while teaching. The first author has taught IE303 Modeling and Methods in Optimization for Bilkent University students for longer than 20 years. A graduate student (a PhD candidate) assistant joined next and started compiling solved problems to be used in exams, quizzes, and homework assignments. The first author added some problems of his own. The result is this book. There are not many books out there dedicated to problems in integer optimization and related topics. The book focuses on the topics covered in IE303 Modeling and Methods in Optimization, a third year required course for Industrial Engineering students at Bilkent University. However, it should be useful for any undergraduate student in industrial engineering or in related disciplines. These are the motivations behind the preparation of this book.
Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization
doi:10.1137/1.9781611977769
Mustafa Ç. Pınar
Deniz Akkaya
Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization
20231113T01:07:28Z
10.1137/1.9781611977769
https://epubs.siam.org/doi/book/10.1137/1.9781611977769?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied Mathematics

Rough Volatility
https://epubs.siam.org/doi/book/10.1137/1.9781611977783?mi=ab3l03&af=R&pubType=book&target=browse
Rough Volatility. <br/> Since we will never really know why the prices of financial assets move, we should at least make a faithful model of how they move. This was the motivation of Bachelier in 1900, when he wrote in the very first page of his thesis that “contradictory opinions in regard to [price] fluctuations are so diverse that at the same instant buyers believe the market is rising and sellers that it is falling.”1 He went on to propose the first mathematical model of prices: the Brownian motion. He then built an option pricing theory that he compared to empirical data available to him—which already revealed, quite remarkably, what is now called the volatility smile.2 1 https://www.investmenttheory.org/uploads/3/4/8/2/34825752/emhbachelier.pdf 2 Looking at Bachelier's table on page 30, one clearly see a smile that flattens with the maturity of the options, as routinely observed nowadays! As we now understand, this flattening comes from the slow convergence of returns towards Gaussian random variables as the timelag increases.
Rough Volatility. <br/> Since we will never really know why the prices of financial assets move, we should at least make a faithful model of how they move. This was the motivation of Bachelier in 1900, when he wrote in the very first page of his thesis that “contradictory opinions in regard to [price] fluctuations are so diverse that at the same instant buyers believe the market is rising and sellers that it is falling.”1 He went on to propose the first mathematical model of prices: the Brownian motion. He then built an option pricing theory that he compared to empirical data available to him—which already revealed, quite remarkably, what is now called the volatility smile.2 1 https://www.investmenttheory.org/uploads/3/4/8/2/34825752/emhbachelier.pdf 2 Looking at Bachelier's table on page 30, one clearly see a smile that flattens with the maturity of the options, as routinely observed nowadays! As we now understand, this flattening comes from the slow convergence of returns towards Gaussian random variables as the timelag increases.
Rough Volatility
doi:10.1137/1.9781611977783
Rough Volatility
20231218T03:11:26Z
10.1137/1.9781611977783
https://epubs.siam.org/doi/book/10.1137/1.9781611977783?mi=ab3l03&af=R&pubType=book&target=browse
© 2023 by the Society for Industrial and Applied Mathematics