Mathematical theory of computation Books

Book Synopsis"My absolute favorite for this kind of interview preparation is Steven Skiena’s The Algorithm Design Manual. More than any other book it helped me understand just how astonishingly commonplace … graph problems are -- they should be part of every working programmer’s toolkit. The book also covers basic data structures and sorting algorithms, which is a nice bonus. … every 1 – pager has a simple picture, making it easy to remember. This is a great way to learn how to identify hundreds of problem types." (Steve Yegge, Get that Job at Google)"Steven Skiena’s Algorithm Design Manual retains its title as the best and most comprehensive practical algorithm guide to help identify and solve problems. … Every programmer should read this book, and anyone working in the field should keep it close to hand. … This is the best investment … a programmer or aspiring programmer can make." (Harold Thimbleby, Times Higher Education)"It is wonderful to open to a random spot and discover an interesting algorithm. This is the only textbook I felt compelled to bring with me out of my student days.... The color really adds a lot of energy to the new edition of the book!" (Cory Bart, University of Delaware)"The is the most approachable book on algorithms I have." (Megan Squire, Elon University)---This newly expanded and updated third edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficiency. It serves as the primary textbook of choice for algorithm design courses and interview self-study, while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Practical Algorithm Design, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, the Hitchhiker's Guide to Algorithms, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations, and an extensive bibliography. NEW to the third edition: -- New and expanded coverage of randomized algorithms, hashing, divide and conquer, approximation algorithms, and quantum computing -- Provides full online support for lecturers, including an improved website component with lecture slides and videos -- Full color illustrations and code instantly clarify difficult concepts -- Includes several new "war stories" relating experiences from real-world applications -- Over 100 new problems, including programming-challenge problems from LeetCode and Hackerrank. -- Provides up-to-date links leading to the best implementations available in C, C++, and Java Additional Learning Tools: -- Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them -- Exercises include "job interview problems" from major software companies -- Highlighted "take home lessons" emphasize essential concepts -- The "no theorem-proof" style provides a uniquely accessible and intuitive approach to a challenging subject -- Many algorithms are presented with actual code (written in C) -- Provides comprehensive references to both survey articles and the primary literature Written by a well-known algorithms researcher who received the IEEE Computer Science and Engineering Teaching Award, this substantially enhanced third edition of The Algorithm Design Manual is an essential learning tool for students and professionals needed a solid grounding in algorithms. Professor Skiena is also the author of the popular Springer texts, The Data Science Design Manual and Programming Challenges: The Programming Contest Training Manual.Table of ContentsIntroduction to Algorithm DesignAlgorithm AnalysisData StructuresSorting and SearchingDivide and ConquerRandomized Algorithms and HashingGraph TraversalWeighted Graph AlgorithmsCombinatorial Search and Heuristic MethodsDynamic ProgrammingNP-CompletenessDealing with Hard Problems How to Design Algorithms14 A Catalog of Algorithmic Problems 43715 Data Structures 43915.1 Dictionaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44015.2 Priority Queues . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44515.3 Sux Trees and Arrays . . . . . . . . . . . . . . . . . . . . . . . 44815.4 Graph Data Structures . . . . . . . . . . . . . . . . . . . . . . . . 45215.5 Set Data Structures . . . . . . . . . . . . . . . . . . . . . . . . . 45615.6 Kd-Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46016 Numerical Problems 46516.1 Solving Linear Equations . . . . . . . . . . . . . . . . . . . . . . 46716.2 Bandwidth Reduction . . . . . . . . . . . . . . . . . . . . . . . . 47016.3 Matrix Multiplication . . . . . . . . . . . . . . . . . . . . . . . . 47216.4 Determinants and Permanents . . . . . . . . . . . . . . . . . . . 47516.5 Constrained/Unconstrained Optimization . . . . . . . . . . . . . 47816.6 Linear Programming . . . . . . . . . . . . . . . . . . . . . . . . . 48216.7 Random Number Generation . . . . . . . . . . . . . . . . . . . . 48616.8 Factoring and Primality Testing . . . . . . . . . . . . . . . . . . . 49016.9 Arbitrary-Precision Arithmetic . . . . . . . . . . . . . . . . . . . 49316.10Knapsack Problem . . . . . . . . . . . . . . . . . . . . . . . . . . 49716.11Discrete Fourier Transform . . . . . . . . . . . . . . . . . . . . . 50117 Combinatorial Problems 50517.1 Sorting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50617.2 Searching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51017.3 Median and Selection . . . . . . . . . . . . . . . . . . . . . . . . . 51417.4 Generating Permutations . . . . . . . . . . . . . . . . . . . . . . 51717.5 Generating Subsets . . . . . . . . . . . . . . . . . . . . . . . . . . 52117.6 Generating Partitions . . . . . . . . . . . . . . . . . . . . . . . . 52417.7 Generating Graphs . . . . . . . . . . . . . . . . . . . . . . . . . . 52817.8 Calendrical Calculations . . . . . . . . . . . . . . . . . . . . . . . 53217.9 Job Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53417.10Satisability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53718 Graph Problems: Polynomial-Time 54118.1 Connected Components . . . . . . . . . . . . . . . . . . . . . . . 54218.2 Topological Sorting . . . . . . . . . . . . . . . . . . . . . . . . . . 54618.3 Minimum Spanning Tree . . . . . . . . . . . . . . . . . . . . . . . 54918.4 Shortest Path . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55418.5 Transitive Closure and Reduction . . . . . . . . . . . . . . . . . . 55918.6 Matching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56218.7 Eulerian Cycle/Chinese Postman . . . . . . . . . . . . . . . . . . 56518.8 Edge and Vertex Connectivity . . . . . . . . . . . . . . . . . . . . 56816 CONTENTS18.9 Network Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57118.10Drawing Graphs Nicely . . . . . . . . . . . . . . . . . . . . . . . 57418.11Drawing Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57818.12Planarity Detection and Embedding . . . . . . . . . . . . . . . . 58119 Graph Problems: NP-Hard 58519.1 Clique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58619.2 Independent Set . . . . . . . . . . . . . . . . . . . . . . . . . . . 58919.3 Vertex Cover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59119.4 Traveling Salesman Problem . . . . . . . . . . . . . . . . . . . . . 59419.5 Hamiltonian Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . 59819.6 Graph Partition . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60119.7 Vertex Coloring . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60419.8 Edge Coloring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60819.9 Graph Isomorphism . . . . . . . . . . . . . . . . . . . . . . . . . 61019.10Steiner Tree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61419.11Feedback Edge/Vertex Set . . . . . . . . . . . . . . . . . . . . . . 61820 Computational Geometry 62120.1 Robust Geometric Primitives . . . . . . . . . . . . . . . . . . . . 62220.2 Convex Hull . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62620.3 Triangulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63020.4 Voronoi Diagrams . . . . . . . . . . . . . . . . . . . . . . . . . . 63420.5 Nearest Neighbor Search . . . . . . . . . . . . . . . . . . . . . . . 63720.6 Range Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64120.7 Point Location . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64420.8 Intersection Detection . . . . . . . . . . . . . . . . . . . . . . . . 64820.9 Bin Packing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65220.10Medial-Axis Transform . . . . . . . . . . . . . . . . . . . . . . . . 65520.11Polygon Partitioning . . . . . . . . . . . . . . . . . . . . . . . . . 65820.12Simplifying Polygons . . . . . . . . . . . . . . . . . . . . . . . . . 66120.13Shape Similarity . . . . . . . . . . . . . . . . . . . . . . . . . . . 66420.14Motion Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . 66720.15Maintaining Line Arrangements . . . . . . . . . . . . . . . . . . . 67120.16Minkowski Sum . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67421 Set and String Problems 67721.1 Set Cover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67821.2 Set Packing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68221.3 String Matching . . . . . . . . . . . . . . . . . . . . . . . . . . . 68521.4 Approximate String Matching . . . . . . . . . . . . . . . . . . . . 68821.5 Text Compression . . . . . . . . . . . . . . . . . . . . . . . . . . 69321.6 Cryptography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69721.7 Finite State Machine Minimization . . . . . . . . . . . . . . . . . 70221.8 Longest Common Substring/Subsequence . . . . . . . . . . . . . 70621.9 Shortest Common Superstring . . . . . . . . . . . . . . . . . . . . 709CONTENTS 1722 Algorithmic Resources 71322.1 Algorithm Libraries . . . . . . . . . . . . . . . . . . . . . . . . . 71322.1.1 LEDA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71322.1.2 CGAL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71422.1.3 Boost Graph Library . . . . . . . . . . . . . . . . . . . . . 71422.1.4 Netlib . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71422.1.5 Collected Algorithms of the ACM . . . . . . . . . . . . . 71522.1.6 GitHub and SourceForge . . . . . . . . . . . . . . . . . . . 71522.1.7 The Stanford GraphBase . . . . . . . . . . . . . . . . . . 71522.1.8 Combinatorica . . . . . . . . . . . . . . . . . . . . . . . . 71622.1.9 Programs from Books . . . . . . . . . . . . . . . . . . . . 71622.2 Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71722.3 Online Bibliographic Resources . . . . . . . . . . . . . . . . . . . 71822.4 Professional Consulting Services . . . . . . . . . . . . . . . . . . 71823 Bibliography 719Index 771

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Book SynopsisHaskell is a purely functional language that allows programmers to rapidly develop clear, concise, and correct software. The language has grown in popularity in recent years, both in teaching and in industry. This book is based on the author''s experience of teaching Haskell for more than twenty years. All concepts are explained from first principles and no programming experience is required, making this book accessible to a broad spectrum of readers. While Part I focuses on basic concepts, Part II introduces the reader to more advanced topics. This new edition has been extensively updated and expanded to include recent and more advanced features of Haskell, new examples and exercises, selected solutions, and freely downloadable lecture slides and example code. The presentation is clean and simple, while also being fully compliant with the latest version of the language, including recent changes concerning applicative, monadic, foldable, and traversable types.Trade Review'The skills you acquire by studying this book will make you a much better programmer no matter what language you use to actually program in.' Erik Meijer, Facebook, from the ForewordReview of previous edition: 'The best introduction to Haskell available. There are many paths towards becoming comfortable and competent with the language but I think studying this book is the quickest path. I urge readers of this magazine to recommend Programming in Haskell to anyone who has been thinking about learning the language.' Duncan Coutts, The Monad.ReaderReview of previous edition: 'Where this book excels is in the order and style of its exposition … With its ripe selection of examples and its careful clarity of exposition, the book is a welcome addition to the introductory functional programming literature.' Journal of Functional ProgrammingTable of ContentsForeword; Preface; Part I. Basic Concepts: 1. Introduction; 2. First steps; 3. Types and classes; 4. Defining functions; 5. List comprehensions; 6. Recursive functions; 7. Higher-order functions; 8. Declaring types and classes; 9. The countdown problem; Part II. Going Further: 10. Interactive programming; 11. Unbeatable tic-tac-toe; 12. Monads and more; 13. Monadic parsing; 14. Foldables and friends; 15. Lazy evaluation; 16. Reasoning about programs; 17. Calculating compilers; Appendix A. Selected solutions; Appendix B. Standard prelude; Bibliography; Index.

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Book SynopsisThis introductory graduate level text provides a relatively quick path to a special topic in classical differential geometry: principal bundles. While the topic of principal bundles in differential geometry has become classic, even standard, material in the modern graduate mathematics curriculum, the unique approach taken in this text presents the material in a way that is intuitive for both students of mathematics and of physics. The goal of this book is to present important, modern geometric ideas in a form readily accessible to students and researchers in both the physics and mathematics communities, providing each with an understanding and appreciation of the language and ideas of the other. Trade Review“He has written a book about principal bundles in the classical sense which is of great interest in and of itself … . a textbook which can be used in an advanced one-year course or for self-learning. … the book is also interesting for a physicist, because one can find the geometric basis of many mathematical tools used in physics. … reviewer has greatly enjoyed reading the book and acknowledges the author’s bravery in writing another text on differential geometry!” (Fernando Etayo Gordejuela, Mathematical Reviews, November, 2015)“The present book deals with principle bundles and their relevance in physics with a ground work on differential geometry. … The book will be helpful to the graduate and under graduate students of mathematics and physics. It can also be an informative hand book of the researchers in differential geometry and physics.” (Uday Chand De, zbMATH 1321.53004, 2015)Table of ContentsIntroduction.- Basics of Manifolds.- Vector Bundles.- Vectors and Covectors.- Differential Forms.- Lie Derivatives.- Lie Groups.- Frobenius Theorem.- Principle Bundles.- Connections on Principle Bundles.- Curvature of a Connection.- Classical Electromagnetism.- Yang-Mills Theory.- Gauge Theory.- The Dirac Monopole.- Instantons.- What Next?.- Discussion of the Exercises.

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Book SynopsisProfessor Stephen A. Cook is a pioneer of the theory of computational complexity. His work on NP-completeness and the P vs. NP problem remains a central focus of this field. Cook won the 1982 Turing Award for "his advancement of our understanding of the complexity of computation in a significant and profound way." This volume includes a selection of seminal papers embodying the work that led to this award, exemplifying Cook's synthesis of ideas and techniques from logic and the theory of computation including NP-completeness, proof complexity, bounded arithmetic, and parallel and space-bounded computation. These papers are accompanied by contributed articles by leading researchers in these areas, which convey to a general reader the importance of Cook's ideas and their enduring impact on the research community. The book also contains biographical material, Cook's Turing Award lecture, and an interview. Together these provide a portrait of Cook as a recognized leader and innovator in mathematics and computer science, as well as a gentle mentor and colleague.

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Book SynopsisDeep learning from the ground up using R and the powerful Keras library! In Deep Learning with R, Second Edition you will learn: Deep learning from first principles Image classification and image segmentation Time series forecasting Text classification and machine translation Text generation, neural style transfer, and image generation Deep Learning with R, Second Edition shows you how to put deep learning into action. It's based on the revised new edition of François Chollet's bestselling Deep Learning with Python. All code and examples have been expertly translated to the R language by Tomasz Kalinowski, who maintains the Keras and Tensorflow R packages at RStudio. Novices and experienced ML practitioners will love the expert insights, practical techniques, and important theory for building neural networks. about the technology Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow put deep learning within reach for all R users, even if they have no experience with advanced machine learning or neural networks. This book shows you how to get started on core DL tasks like computer vision, natural language processing, and more using R. what's inside Image classification and image segmentation Time series forecasting Text classification and machine translation Text generation, neural style transfer, and image generation about the reader For readers with intermediate R skills. No previous experience with Keras, TensorFlow, or deep learning is required.

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Book SynopsisThis book describes a fully automated Boolean System and gives special attention to theoretical problems in automatic retrieval of textual information. The book details algorithms in each process in the system, including those that are radically new in the retrieval process and those that are adaptable to the individual.Table of ContentsThe System and Systems Approach. Vital Activities and Needs. Information Crisis and Search for Information. Concept of an Information Retrieval System. Information Retrieval Language. Automatic Indexing of Documents. Automatic Indexing of Search Requests. Storage and Access to Information. Control and Feedback in IR Systems. Evaluation of Information Retrieval. Evaluation of Macroevaluated Objects. Some Directions in the Development of IR Systems. Index.

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Book SynopsisAlgebraic coding theory is a new and rapidly developing subject, motivated by immediate practical applications, but also rich in mathematical structure. This book provides an elementary yet rigorous introduction to the theory of error-correcting codes.

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Book SynopsisThis concise, accessible text provides a thorough introduction to quantum computing - an exciting emergent field at the interface of the computer, engineering, mathematical and physical sciences. Aimed at advanced undergraduate and beginning graduate students in these disciplines, the text is technically detailed and is clearly illustrated throughout with diagrams and exercises. Some prior knowledge of linear algebra is assumed, including vector spaces and inner products. However, prior familiarity with topics such as quantum mechanics and computational complexity is not required.Trade ReviewThe book is spiced with Try Its, brief exercises that engage the readers in problem solving (both with and without mathematics) and help them digest the many counter-intuitive quantum information science and quantum computing concepts. * MathSciNet *Table of ContentsPreface ; 1. Introduction and background ; 2. Linear algebra and the Dirac notation ; 3. Qubits and the framework of quantum mechanics ; 4. A quantum model of computation ; 5. Superdense coding and quantum teleportation ; 6. Introductory quantum algorithms ; 7. Algorithms with super-polynomial speed-up ; 8. Algorithms based on amplitude amplification ; 9. Quantum computational complexity theory and lower bounds ; 10. Quantum error correction ; Appendices ; Bibliography ; Index

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Book SynopsisThis book is a concise introduction to the key mathematical ideas that underpin computer science, continually stressing the application of discrete mathematics to computing. It is suitable for students with little or no knowledge of mathematics, and covers the key concepts in a simple and straightforward way.Table of Contents1. Introduction 2. Logic and Proof 3. Set Theory 4. Relations 5. Functions 6. Combinatorics 7. Graphs 8. Directed Graphs 9. Boolean Algebra Application: Designing a 2-Bit Adder

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Book SynopsisThe challenges of problems from international programming competitions are an effective way to improve your algorithmic and coding skills and understanding. This volume uses international programming competition-type problems to motivate the study of algorithms, programming, and other topics in computer science.Trade Review"Skiena and Revilla's new book 'Programming Challenges: The Programming Contest Training Manual' is just the ticket for those interested in a jumpstart to the world of contest programming. With special emphasis on the international ACM collegiate contests, the book's best feature is each chapter's pithy introduction that demystifies a particular scheme or algorithmic approach. The ensemble of these explications coupled with the contest strategy guidelines in the appendix can enable a novice to enhance contest results dramatically in a short time simply by solving the suggested exercises in each chapter. Even contest veterans are likely to be able to find a nugget or two in the explanations and strategies. "Presented in a logical order (contest programming has over a dozen different primary attacks), the book guides readers not only through the techniques and algorithms required but also through a huge set of problems that can be used for training. Solutions can be submitted to Valladolid University's online trainer for quick feedback and reinforcement. "If you're the sort who likes to have a single volume that covers the vast majority of a field, you'll love Skiena and Revilla's new tome." --Rob Kolstad, Ph.D., Head Coach, USA Computing OlympiadTable of Contents* Getting started * Data structures * Strings * Sorting * Arithmetic and algebra * Combinatorics * Number theory * Backtracking * Graph traversal * Graph algorithms * Dynamic programming * Grids * Geometry * Computational geometry * Appendix * Index

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Book Synopsis1 Naive Set Theory.- 1.1 What is a Set?.- 1.2 Operations on Sets.- 1.3 Notation for Sets.- 1.4 Sets of Sets.- 1.5 Relations.- 1.6 Functions.- 1.7 Well-Or der ings and Ordinals.- 1.8 Problems.- 2 The ZermeloFraenkel Axioms.- 2.1 The Language of Set Theory.- 2.2 The Cumulative Hierarchy of Sets.- 2.3 The ZermeloFraenkel Axioms.- 2.4 Classes.- 2.5 Set Theory as an Axiomatic Theory.- 2.6 The Recursion Principle.- 2.7 The Axiom of Choice.- 2.8 Problems.- 3 Ordinal and Cardinal Numbers.- 3.1 Ordinal Numbers.- 3.2 Addition of Ordinals.- 3.3 Multiplication of Ordinals.- 3.4 Sequences of Ordinals.- 3.5 Ordinal Exponentiation.- 3.6 Cardinality, Cardinal Numbers.- 3.7 Arithmetic of Cardinal Numbers.- 3.8 Regular and Singular Cardinals.- 3.9 Cardinal Exponentiation.- 3.10 Inaccessible Cardinals.- 3.11 Problems.- 4 Topics in Pure Set Theory.- 4.1 The Borel Hierarchy.- 4.2 Closed Unbounded Sets.- 4.3 Stationary Sets and Regressive Functions.- 4.4 Trees.- 4.5 Extensions of Lebesgue Measure.- 4.6 A ReTable of ContentsPreface; 1. Naïve Set Theory; 2. The Zermelo-Fraenkel Axioms; 3. Ordinal and Cardinal Numbers; 4. Topics in Pure Set Theory; 5. The Axiom of Constructibility; 6. Independence Proofs in Set Theory; 7. Non-Well-Founded Set Theory; Bibliography; Glossary of Symbols; Index

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Book SynopsisA classic book about life in a two-dimensional universe, written by a well-known author. Now brought back into print in this revised and updated edition, the book is written within the great tradition of Abbott's Flatland, and Hinton's famous Sphereland.Table of Contents1 Arde.- 2 A House by the Sea.- 3 On Fiddib Har.- 4 Walking to Is Felblt.- 5 City Below Ground.- 6 The Trek.- 7 The Punizlan Institute.- 8 Traveling on the Wind.- 9 High on Dahl Radam.- 10 Drabk the Sharak of Okbra.- 11 Higher Dimensions.- Ardean Science and Technology.- Acknowledgments.

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Book SynopsisA unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, Trade Review “In conclusion, I found reading Metaheuristics: From Design to Implementation to be pleasant and enjoyable. I particularly recommend it as a reference for researchers and students of computer science or operations research who want a global outlook of metaheuristics methods. It would also be extremely useful for introducing graduate and PhD students who are new to the field of heuristics and metaheuristics to the amazing world of the designing of these procedures.” (Informs, 1 July 2012) "It will be an indispensable text for advanced undergraduate and graduate students in computer science, operations research, applied mathematics, control, business and management and engineering." (Zentralblatt MATH, 2010) Table of ContentsPreface. Acknowledgments. Glossary. 1 Common Concepts for Metaheuristics. 1.1 Optimization Models. 1.2 Other Models for Optimization. 1.3 Optimization Methods. 1.4 Main Common Concepts for Metaheuristics. 1.5 Constraint Handling. 1.6 Parameter Tuning. 1.7 Performance Analysis of Metaheuristics. 1.8 Software Frameworks for Metaheuristics. 1.9 Conclusions. 1.10 Exercises. 2 Single-Solution Based Metaheuristics. 2.1 Common Concepts for Single-Solution Based Metaheuristics. 2.2 Fitness Landscape Analysis. 2.3 Local Search. 2.4 Simulated Annealing. 2.5 Tabu Search. 2.6 Iterated Local Search. 2.7 Variable Neighborhood Search. 2.8 Guided Local Search. 2.9 Other Single-Solution Based Metaheuristics. 2.10 S-Metaheuristic Implementation Under ParadisEO. 2.11 Conclusions. 2.12 Exercises. 3 Population-Based Metaheuristics. 3.1 Common Concepts for Population-Based Metaheuristics. 3.2 Evolutionary Algorithms. 3.3 Common Concepts for Evolutionary Algorithms. 3.4 Other Evolutionary Algorithms. 3.5 Scatter Search. 3.6 Swarm Intelligence. 3.7 Other Population-Based Methods. 3.8 P-metaheuristics Implementation Under ParadisEO. 3.9 Conclusions. 3.10 Exercises. 4 Metaheuristics for Multiobjective Optimization. 4.1 Multiobjective Optimization Concepts. 4.2 Multiobjective Optimization Problems. 4.3 Main Design Issues of Multiobjective Metaheuristics. 4.4 Fitness Assignment Strategies. 4.5 Diversity Preservation. 4.6 Elitism. 4.7 Performance Evaluation and Pareto Front Structure. 4.8 Multiobjective Metaheuristics Under ParadisEO. 4.9 Conclusions and Perspectives. 4.10 Exercises. 5 Hybrid Metaheuristics. 5.1 Hybrid Metaheuristics. 5.2 Combining Metaheuristics with Mathematical Programming. 5.3 Combining Metaheuristics with Constraint Programming. 5.4 Hybrid Metaheuristics with Machine Learning and Data Mining. 5.5 Hybrid Metaheuristics for Multiobjective Optimization. 5.6 Hybrid Metaheuristics Under ParadisEO. 5.7 Conclusions and Perspectives. 5.8 Exercises. 6 Parallel Metaheuristics. 6.1 Parallel Design of Metaheuristics. 6.2 Parallel Implementation of Metaheuristics. 6.3 Parallel Metaheuristics for Multiobjective Optimization. 6.4 Parallel Metaheuristics Under ParadisEO. 6.5 Conclusions and Perspectives. 6.6 Exercises. Appendix: UML and C++. A.1 A Brief Overview of UML Notations. A.2 A Brief Overview of the C++ Template Concept. References. Index.

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Book SynopsisCovering classification and regression, Statistical Learning is the first of its kind to use visualization techniques to identify, test, and analyze classifiers for their most accurate exploration of data.Trade Review“Altogether, the book provides a very nice overview of nonparametric and semiparametric regression methods with interesting applications to problems in quantitative finance.” (Mathematical Reviews, 1 October 2015) Table of ContentsPreface xvii Introduction xix I.1 Estimation of Functionals of Conditional Distributions xx I.2 Quantitative Finance xxi I.3 Visualization xxi I.4 Literature xxiii PART I METHODS OF REGRESSION AND CLASSIFICATION 1 Overview of Regression and Classification 3 1.1 Regression 3 1.2 Discrete Response Variable 29 1.3 Parametric Family Regression 33 1.4 Classification 37 1.5 Applications in Quantitative Finance 42 1.6 Data Examples 52 1.7 Data Transformations 53 1.8 Central Limit Theorems 58 1.9 Measuring the Performance of Estimators 61 1.10 Confidence Sets 73 1.11 Testing 75 2 Linear Methods and Extensions 77 2.1 Linear Regression 78 2.2 Varying Coefficient Linear Regression 97 2.3 Generalized Linear and Related Models 102 2.4 Series Estimators 107 2.5 Conditional Variance and ARCH models 111 2.6 Applications in Volatility and Quantile Estimation 115 2.7 Linear Classifiers 124 3 Kernel Methods and Extensions 127 3.1 Regressogram 129 3.2 Kernel Estimator 130 3.3 Nearest Neighborhood Estimator 147 3.4 Classification with Local Averaging 148 3.5 Median Smoothing 151 3.6 Conditional Density Estimators 152 3.7 Conditional Distribution Function Estimation 158 3.8 Conditional Quantile Estimation 160 3.9 Conditional Variance Estimation 162 3.10 Conditional Covariance Estimation 176 3.11 Applications in Risk Management 181 3.12 Applications in Portfolio Selection 205 4 Semiparametric and Structural Models 229 4.1 Single Index Model 230 4.2 Additive Model 234 4.3 Other Semiparametric Models 237 5 Empirical Risk Minimization 241 5.1 Empirical Risk 243 5.2 Local Empirical Risk 247 5.3 Support Vector Machines 257 5.4 Stagewise Methods 259 5.5 Adaptive Regressograms 264 PART II VISUALIZATION 6 Visualization of Data 277 6.1 Scatter Plots 278 6.2 Histogram and Kernel Density Estimator 282 6.3 Dimension Reduction 284 6.4 Observations as Objects 288 7 Visualization of Functions 295 7.1 Slices 296 7.2 Partial Dependence Functions 296 7.3 Reconstruction of Sets 299 7.4 Level Set Trees 303 7.5 Unimodal Densities 326 7.5.1 Probability Content of Level Sets 327 7.5.2 Set Visualization 328 Appendix A: R Tutorial 329 A.1 Data Visualization 329 A.2 Linear Regression 331 A.3 Kernel Regression 332 A.4 Local Linear Regression 341 A.5 Additive Models: Backfitting 344 A.6 Single Index Regression 345 A.7 Forward Stagewise Modeling 347 A.8 Quantile Regression 349 References 351 Author Index 361 Topic Index 365

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Book SynopsisThis new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing. The book is comprised of four main parts spanning the field: Optimization Integration and Simulation Bootstrapping Density Estimation and Smoothing Within these sections,each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods. The new edition includes updated coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data. The book website now includes comprehensive R code for the entire book. There are extensive exercises, real examples, and helpful insights about how to use the methods in practice.Table of ContentsPREFACE xv ACKNOWLEDGMENTS xvii 1 REVIEW 1 1.1 Mathematical Notation 1 1.2 Taylor’s Theorem and Mathematical Limit Theory 2 1.3 Statistical Notation and Probability Distributions 4 1.4 Likelihood Inference 9 1.5 Bayesian Inference 11 1.6 Statistical Limit Theory 13 1.7 Markov Chains 14 1.8 Computing 17 PART I OPTIMIZATION 2 OPTIMIZATION AND SOLVING NONLINEAR EQUATIONS 21 2.1 Univariate Problems 22 2.2 Multivariate Problems 34 Problems 54 3 COMBINATORIAL OPTIMIZATION 59 3.1 Hard Problems and NP-Completeness 59 3.2 Local Search 65 3.3 Simulated Annealing 68 3.4 Genetic Algorithms 75 3.5 Tabu Algorithms 85 Problems 92 4 EM OPTIMIZATION METHODS 97 4.1 Missing Data, Marginalization, and Notation 97 4.2 The EM Algorithm 98 4.3 EM Variants 111 Problems 121 PART II INTEGRATION AND SIMULATION 5 NUMERICAL INTEGRATION 129 5.1 Newton–Côtes Quadrature 129 5.2 Romberg Integration 139 5.3 Gaussian Quadrature 142 5.4 Frequently Encountered Problems 146 Problems 148 6 SIMULATION AND MONTE CARLO INTEGRATION 151 6.1 Introduction to the Monte Carlo Method 151 6.2 Exact Simulation 152 6.3 Approximate Simulation 163 6.4 Variance Reduction Techniques 180 Problems 195 7 MARKOV CHAIN MONTE CARLO 201 7.1 Metropolis–Hastings Algorithm 202 7.2 Gibbs Sampling 209 7.3 Implementation 218 Problems 230 8 ADVANCED TOPICS IN MCMC 237 8.1 Adaptive MCMC 237 8.2 Reversible Jump MCMC 250 8.3 Auxiliary Variable Methods 256 8.4 Other Metropolis–Hastings Algorithms 260 8.5 Perfect Sampling 264 8.6 Markov Chain Maximum Likelihood 268 8.7 Example: MCMC for Markov Random Fields 269 Problems 279 PART III BOOTSTRAPPING 9 BOOTSTRAPPING 287 9.1 The Bootstrap Principle 287 9.2 Basic Methods 288 9.3 Bootstrap Inference 292 9.4 Reducing Monte Carlo Error 302 9.5 Bootstrapping Dependent Data 303 9.6 Bootstrap Performance 315 9.7 Other Uses of the Bootstrap 316 9.8 Permutation Tests 317 Problems 319 PART IV DENSITY ESTIMATION AND SMOOTHING 10 NONPARAMETRIC DENSITY ESTIMATION 325 10.1 Measures of Performance 326 10.2 Kernel Density Estimation 327 10.3 Nonkernel Methods 341 10.4 Multivariate Methods 345 Problems 359 11 BIVARIATE SMOOTHING 363 11.1 Predictor–Response Data 363 11.2 Linear Smoothers 365 11.3 Comparison of Linear Smoothers 377 11.4 Nonlinear Smoothers 379 11.5 Confidence Bands 384 11.6 General Bivariate Data 388 Problems 389 12 MULTIVARIATE SMOOTHING 393 12.1 Predictor–Response Data 393 12.2 General Multivariate Data 413 Problems 416 DATA ACKNOWLEDGMENTS 421 REFERENCES 423 INDEX 457

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Book SynopsisThis edition includes developments in chaos theory, with new chapters that tie in with innovations such as fuzzy logic, neural nets and artificial intelligence as they relate to finance.Table of ContentsTHE NEW PARADIGM. Introduction: Life Can Be So Complicated. Random Walks and Efficient Markets. The Failure of the Linear Paradigm. Markets and Chaos: Chance and Necessity. FRACTAL STRUCTURE IN THE CAPITAL MARKETS. Introduction to Fractals. The Fractal Dimension. Fractal Time Series-Biased Random Walks. R/S Analysis of the Capital Markets. Fractal Statistics. Fractals and Chaos. NONLINEAR DYNAMICS. Introduction to Nonlinear Dynamic Systems. Dynamic Analysis of Time Series. Dynamic Analysis of the Capital Markets. LIVING WITH COMPLEXITY. The Coherent Market Hypothesis. Fractional Truth: Fuzzy Logic and Behavioral Finance. Applying Chaos and Nonlinear Methods. What Lies Ahead: Toward a More General Approach. About the Diskette. Appendices. Bibliography. Glossary. Index.

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Book SynopsisA unique, integrated treatment of computer modeling and simulation The future of science belongs to those willing to make the shift to simulation-based modeling, predicts Rice Professor James Thompson, a leading modeler and computational statistician widely known for his original ideas and engaging style. He discusses methods, available to anyone with a fast desktop computer, for integrating simulation into the modeling process in order to create meaningful models of real phenomena. Drawing from a wealth of experience, he gives examples from trading markets, oncology, epidemiology, statistical process control, physics, public policy, combat, real-world optimization, Bayesian analyses, and population dynamics. Dr. Thompson believes that, so far from liberating us from the necessity of modeling, the fast computer enables us to engage in realistic models of processes in , for example, economics, which have not been possible earlier because simple stochastic models in the forward temporal Trade ReviewWith the advent of faster computers with comparatively large storage facilities, simulation-based modeling is rapidly being adopted as an alternative approach to conventional top-down, assumptions-based, continuous, stochastic and discrete differential equation modeling. Thompson offers an interesting exposition to the art of simulation, and views "simulation approach" to modeling as a paradigm for realistic evolutionary modeling. The book is written in a very casual style, and background knowledge in statistics is all that is required to grasp the material contained therein. Thompson begins with an exposition of the generation of randomnumbers and then delves into a variety of special topics, including models for stocks and derivatives, optimization and estimation in a noisy world, Monte-Carlo solutions to differential equations, simulation assessment of multivariate and robust procedures in statistical process control, resampling-based tests, and some exposition to modeling the AIDS epidemic. Several useful algorithms, problem sets, and references to standard simulation packages are provided. Short chapter bibliographies; wide range of examples. The book could be used as a resource for beginning graduate students and professionals in applied statistics, computer science, economics and finance, engineering, and the natural sciences. Highly recommended. Graduate students; faculty; professionals. (CHOICE, April 2001, Vol. 38, No. 8) "...an eclectic survey of computing methods...lively and interesting...the wide variety of example certainly helps bring the material to life." (Journal of the American Statistical Association, Vol. 97, No. 457, March 2002) "...a very useful and entertaining book...a great reference book...contains some valuable material and philosophy that is unavailable anywhere else." (IIE Transactions) "...often entertaining...the level of detain and relevance is appropriate...a worthwhile read for model builders comfortable with both mathematics and simulation." (Complexity, Vol. 7, No. 2, 2002)Table of ContentsThe Generation of "Random" Numbers. Random Quadrature. Monte Carlo Solutions of Differential Equations. Markov Chains, Poisson Processes and Linear Equations. SIMEST, SIMDAT, and Pseudoreality. Models for Stocks and Derivatives. Simulation Assessment of Multivariate and Robust Procedures in Statistical Process Control. Noise and Chaos. Bayesian Approaches. Resampling Based Tests. Optimization and Estimation in a Noisy World. Modeling the USA AIDS Epidemic: Exploration, Simulation and Conjecture. Appendices. Index.

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Book SynopsisReinforcing concepts with frequent exercises and extended applications, this introduction to the theoretical and computational aspects of linear algebra uses the MATLAB software to master the basic algorithms and to increase the speed and efficiency of computations.Table of ContentsMatrix Algebra. Vector Spaces and Linear Transformations. Orthogonality and Projections. Eigenvalues and Eigenvectors. The Spectral Theorem and Applications. Normal Forms. Appendices. Bibliography. Index.

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Book SynopsisThere are many situations in science and engineering where complex output data from a given system is used to formulate a model of how that system operates, or to simulate its response to different inputs. Applications include control, decision theory, and the emerging fields of bioinformatics.Trade Review"To cope with real world uncertainties and provide a philosophical and practical guide...several methodologies are presented..." (SciTech Book News, Vol. 25, No. 4, December 2001) "...certainly a book that should be in the library of any institution where research and advanced study in fuzzy systems are carried out." (Choice, Vol. 39, No. 7, March 2002) "...well organized, easy to read, and self-contained.... I would recommend it to anyone interested in self-study of the basic ideas of fuzzy systems..." (International Journal of General Systems, Vol. 31, No. 6, 2002)Table of ContentsPreface. Acknowledgments. Introduction. System Analysis. Uncertainty Techniques. Learning from Data: System Identification. Propositions as Subsets of the Data Space. Fuzzy Systems and Identification. Random-Set Modelling and Identification. Certain Uncertainty. Fuzzy Inference Engines. Fuzzy Classification. Fuzzy Control. Fuzzy Mathematics. Summary. Appendices. Index.

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Book SynopsisA complete, highly accessible introduction to one of today's most exciting areas of applied mathematics One of the youngest, most vital areas of applied mathematics, combinatorial optimization integrates techniques from combinatorics, linear programming, and the theory of algorithms.Table of ContentsProblems and Algorithms. Optimal Trees and Paths. Maximum Flow Problems. Minimum-Cost Flow Problems. Optimal Matchings. Integrality of Polyhedra. The Traveling Salesman Problem. Matroids. NP and NP-Completeness. Appendix. Bibliography. Index.

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Book SynopsisThe process of solving large problems by breaking them down into smaller, more simple problems that have identical forms. Thinking Recursively: A small text to solve large problems. Concentrating on the practical value of recursion. this text, the first of its kind, is essential to computer science students' education.Table of ContentsThe Idea of Recursion. Mathematical Preliminaries. Recursive Functions. The Procedural Approach. The Tower of Hanoi. Permutations. Sorting. Intelligent Algorithms. Graphical Applications. Recursive Data. Implementation of Recursion.

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Book SynopsisModern software places increasing reliance on dynamic memory allocation, but its direct management is not only notoriously error--prone. Garbage collection eliminates many of these bugs. This reference presents each of the most important algorithms in detail, often with illustrations of its characteristic features and animations of its use.Table of ContentsThe Classical Algorithms. Reference Counting. Mark-Sweep Garbage Collection. Mark-Compact Garbage Collection. Copying Garbage Collection. Generational Garbage Collection. Incremental and Concurrent Garbage Collection. Garbage Collection for C. Garbage Collection for C++. Cache-Conscious Garbage Collection. Distributed Garbage Collection. Glossary. Bibliography. Index.

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Book SynopsisThe aim of this work is to give breadth and depth to the C++ programmer's existing experience of the language. It presents a large number of algorithms, each of them implemented as ready-to-run (and standalone) programs.Table of ContentsSome Aspects of Programming in C++. Arithmetic. Sorting Arrays and Files. Stacks, Queues and Lists. Searching and String Processing. Binary Trees. B-trees. Tries, Priority Queues and File Compression. Graphs. Some Combinatorial Algorithms. Fundamentals of Interpreters and Compilers. Appendix. Bibliography. Index.

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Book SynopsisThis book presents the basic scientific computing methods for the solution of partial differential equations (PDEs) as they occur in engineering problems. Programming codes in Fortran and C are included for each problem.Table of ContentsSome Partial Differential Equations. PROGRAMMING THE MODEL PROBLEM BY A FINITE ELEMENT METHOD. Introduction to the Finite Element Method: Energy Minimisation. Finite Element Method: Variational Formulation and Direct Methods. Finite Element Method: Optimisation of the Method. GENERAL ELLIPTIC PROBLEMS AND EVOLUTION PROBLEMS. Finite Element Method for General Elliptic Problems. Non-symmetric or Non-linear Partial Differential Equations. Evolution Problems: Finite Differences in Time. COMPLEMENTS ON NUMERICAL METHODS. Integral Methods for the Laplacian. Some Algorithms for Parallel Computing. Bibliography. Index.

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Book SynopsisBuilding on the basic tools presented in the first volume, this second volume of Foundations of Cryptography contains a rigorous and systematic treatment of three basic applications: Encryption, Signatures, and General Cryptographic Protocols. It is suitable for use in a graduate course on cryptography and as a reference book for experts.Trade ReviewReview of the hardback: 'This is a very complete introduction to the basics of modern complexity-theoretic cryptography. It is a solid foundation for understanding much of the current work in this area.' ACM SIGACT NewsTable of ContentsList of figures; Preface; Acknowledgements; 5. Encryption schemes; 6. Digital signatures and message authentication; 7. General cryptographic protocols; Appendix C: corrections and additions to volume I; Bibliography; Index.

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Book SynopsisA comprehensive 2003 treatment of term rewriting systems from an elementary to an advanced level. Much of this material appeared here for the first time in book form. Ideal for teaching or research, it features numerous exercises with selected solutions on the web, an extensive bibliography and a chapter on applications.Trade Review'The book presents the state of the art of rewriting techniques, it gives (or scratches) proofs on a very precise level and gives hints to historical sources of the results and to further readings, so it is highly recommended to researchers working in this area.' Zentralblatt für Mathematik'… has extensive material … suffice it to say that this book is indispensable for a any serious student of rewriting.' Journal of TLP'… it will soon be a compulsory reference for anyone working in the area.' Journal of Functional ProgrammingTable of Contents1. Abstract reduction systems; 2. First-order term rewriting systems; 3. Examples of TRSs and special rewriting formats; 4. Orthogonality; 5. Properties of rewriting: decidability and modularity; 6. Termination; 7. Completion of equational specifications; 8. Equivalence of reductions; 9. Strategies; 10. Lambda calculus; 11. Higher order rewriting; 12. Infinitary rewriting; 13. Term graph rewriting; 14. Advanced ARS theory; 15. Rewriting based languages and systems; 16. Mathematical background.

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Book SynopsisThis book provides a unified understanding of the use of generating functions for labelled and unlabelled structures. Applications include graphical enumeration, Polya theory and analysis of data structures in computer science, special functions, functional equations, asymptotic analysis, and differential equations.Trade Review'This book can serve as an introduction to the subject; it will also be an extremely valuable reference book.' International Mathematical News' … the first complete presentation in English of the combinatorial theory of species.' L'Enseignment Mathématique' … a comprehensive account.' Zentralblatt für Mathematik und ihre GrenzgebieteTable of Contents1. Introduction to species of structures; 2. Complements on species of structures; 3. Combinatorial functional equations; 4. Complements on types of structures; 5. Species on totally ordered sets.

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Book SynopsisTyped lambda calculus is used in functional programming (Haskell, Clean) and proof assistants (Coq, Isabelle, HOL), which are used to design and verify IT products and mathematical proofs. This book reveals unexpected mathematical beauty in three classes of typing: simple types, recursive types and intersection types. Numerous exercises are provided.Trade Review'The book has a place in undergraduate libraries because of its uniquely comprehensive, if theoretical, treatment of a timely, widely important subject. Recommended.' D. V. Feldman, Choice'The authors have produced a well-written, organised and comprehensive account of three important type systems. These systems' properties have been rich sources of interest to logicians for many years; their problems are not all solved, and in future work this book will almost certainly become a standard reference about them. It will also allow the more mathematically inclined computer scientist to obtain a deeper understanding of the principles behind some of the higher order languages in current use.' Bulletin of the London Mathematical SocietyTable of ContentsList of contributors; Preface; Introduction; Part I. Simple Types: 1. The simply typed lambda calculus; 2. Properties; 3. Tools; 4. Definability, unification and matching; 5. Extensions; 6. Applications; Part II. Recursive Types: 7. The systems; 8. Properties of recursive types; 9. Properties of terms with types; 10. Models; 11. Applications; Part III. Intersection Types: 12. An exemplary system; 13. Type assignment systems; 14. Basic properties; 15. Type and lambda structures; 16. Filter models; 17. Advanced properties and applications; Bibliography; Symbol index; Names index; Definitions index.

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Book SynopsisThe is an introduction to simple type theory, exploring the relationship between proof and calculation. Each of its 52 sections ends with a set of exercises, some 200 in total. These are designed to help the reader get to grips with the subject. An appendix contains complete solutions to them.Trade Review'A well-written introduction to proof theory and its connections with computability.' Leon Harkleroad, Zentralblatt für Mathematik'… recommended for the student or researcher who's been exposed to bits and pieces of the Curry-Howard correspondence, but wants a sharper idea of the big picture and is willing to work through the exercises to see how the details fit together. Simmons has succeeded in pulling together the main fruits of the correspondence for simple types in a single text. … It can't be emphasized enough that the great thing about this book is its many well-chosen completely solved exercises. This alone makes it a valuable text, especially for self-study.' ACM SIGACT NewsTable of ContentsIntroduction; Preview; Part I. Development and Exercises: 1. Derivation systems; 2. Computation mechanisms; 3. The typed combinator calculus; 4. The typed l-calculus; 5. Substitution algorithms; 6. Applied l-calculi; 7. Multi-recursive arithmetic; 8. Ordinals and ordinal notation; 9. Higher order recursion; Part II. Solutions: A. Derivation systems; B. Computation mechanisms; C. The typed combinator calculus; D. The typed l-calculus; E. Substitution algorithms; F. Applied l-calculi; G. Multi-recursive arithmetic; H. Ordinals and ordinal notation; I. Higher order recursion; Postview; Bibliography; Commonly used symbols; Index.

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Book SynopsisThis new edition of Introduction to Lattices and Order presents a radical reorganization and updating, though its primary aim is unchanged. The explosive development of theoretical computer science in recent years has, in particular, influenced the book's evolution: a fresh treatment of fixpoints testifies to this and Galois connections now feature prominently. An early presentation of concept analysis gives both a concrete foundation for the subsequent theory of complete lattices and a glimpse of a methodology for data analysis that is of commercial value in social science. Classroom experience has led to numerous pedagogical improvements and many new exercises have been added. As before, exposure to elementary abstract algebra and the notation of set theory are the only prerequisites, making the book suitable for advanced undergraduates and beginning graduate students. It will also be a valuable resource for anyone who meets ordered structures.Trade Review'Recommended for every academic mathematics collection.' Choice'… an excellent introductory textbook on ordered sets and lattices and it is intended for undergraduate and beginning graduate students in mathematics.' Vaclav Slavic, Zentralblatt für Mathematik'I used Introduction to Lattices and Order as the sole textbook in a one semester course. The students enrolled were a heterogeneous group including modestly prepared undergraduates, well trained graduate students, and a few applications-oriented computer science students … In short, the textbook was a success.' Joel Berman, Australian Mathematical Society Gazette'… a well-written, satisfying, informative, and stimulating account of applications that are of great interest, particularly in computer science and social science … it will surely become a classic.' Mathematical Reviews'Altogether, this is a great book. It would be interesting (and educational) to give a course based on it - almost makes me wish I hadn't retired!' Australian Mathematical Society Gazette'… a valuable source to anyone who needs to use ordered structures in any context.' EMS Newsletter'It can be recommended as a valuable source to anyone who needs to use ordered structures in any context.' European Mathematical Society'The book is written in a very engaging and fluid style. The understanding of the content is aided tremendously by the very large number of beautiful lattice diagrams … The book provides a wonderful and accessible introduction to lattice theory, of equal interest to both computer scientists and mathematicians.' Jonathan Cohen, SIGACT NewsTable of ContentsPreface; Preface to the first edition; 1. Ordered sets; 2. Lattices and complete lattices; 3. Formal concept analysis; 4. Modular, distributive and Boolean lattices; 5. Representation theory: the finite case; 6. Congruences; 7. Complete lattices and Galois connections; 8. CPOs and fixpoint theorems; 9. Domains and information systems; 10. Maximality principles; 11. Representation: the general case; Appendix A. A topological toolkit; Appendix B. Further reading; Notation index; Index.

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Book SynopsisAutomata theory lies at the foundation of computer science, and is vital to a theoretical understanding of how computers work and what constitutes formal methods. This treatise gives a rigorous account of the topic and illuminates its real meaning by looking at the subject in a variety of ways. The first part of the book is organised around notions of rationality and recognisability. The second part deals with relations between words realised by finite automata, which not only exemplifies the automata theory but also illustrates the variety of its methods and its fields of application. Many exercises are included, ranging from those that test the reader, to those that are technical results, to those that extend ideas presented in the text. Solutions or answers to many of these are included in the book.Trade Review'… a rich exposition … expertly translated by Reuben Thomas … its motivating ideas and substantive cross-currents fill almost every page … Nothing seems to be missing … should be on the shelf of every serious student and professional. It will enjoy a very long stay on my own.' Computing ReviewsTable of ContentsForeword; 0. Fundamental structures; 1. The simplest possible machine; 2. The power of algebra; 3. The pertinence of enumeration; 4. The richness of transducers; 5. The simplicity of functional transducers; Bibliography; Index.

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Book SynopsisWritten for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that integrates literature from several fields into a coherent source for teaching and reference in applications including robotics, computational biology, computer graphics, manufacturing, aerospace applications and medicine.Trade Review'This is a terrific book, a milestone in the robotics literature.' Matt Mason, Director of The Carnegie Mellon Robotics Institute'Motion planning is an important field of research with applications in such diverse terrains as robotics, molecular modeling, virtual environments, and games. Over the past two decades a huge number of techniques have been developed, all with their merits and shortcomings. The book by Steve LaValle gives an excellent overview of the current state of the art in the field. It should lie on the desk of everybody that is involved in motion planning research or the use of motion planning in applications.' Mark Overmars, Utrecht University'A great book at the junction where Robotics, Artificial Intelligence, and Control are crossing their paths. For many problems you will find in-depth discussion and algorithms; for virtually all others in the field, an intriguing introduction to make you at ease and entice you to further probing the matter.' Antonio Bicchi, della Università di Pisa'Since the early 90s, Latombe's book has been the authoritative source for students and researchers working on motion planning problems in robotics. During the succeeding decade and half, the motion planning field moved forward with significant developments. LaValle's book picks up the field where Latombe's book left it, describing in detail major developments such as probabilistic roadmaps, manipulation, and coverage planning. Moreover, the book describes a fundamental generalization of configuration spaces to information spaces. The chapters on information spaces appear here for the first time, making them accessible to students and researchers who wish to tackle progressively more challenging real-world motion planning problems in robotics.' Elon Rimon, Technion'Planning Algorithms is a daring title. It aims at being ecumenical gathering students and their professors scattered in various departments of Engineering and calling them to share the same mathematical foundations. The story starts with motion planning algorithms. Steve LaValle's deep extensive understanding and his effective expertise in that area are shared in this book. They allow the author to go further and to generalize the famous configuration space of the piano mover problem into the information space. This is the core of the title ambition. All the seminal material born with Robotics, Artificial Intelligence and Control, and developed for more than thirty years in a sparse way, are there uniquely unified. The book is not a catalogue of methods. It is the coherent view of a single researcher. The style is nice making the reading fluent: there is a good balance between informal introduction of concepts and the necessary technical developments. Students, researchers and engineers exploring routes in Artificial Intelligence and Robotics, in Graphics and CAD/CAM, and even Molecular Biology now, will find here amazing computational foundations for their topics.' Jean-Paul Laumond, LAAS-CNRS' … this book really is monumental and well-written piece of work, and although few will have cause to read more than a fraction of its content, at its price it deserves to find its way onto the bookshelves of many of us, as well as being recommended to our students.' ScienceDirectTable of ContentsPart I. Introductory Material: 1. Introduction; 2. Discrete planning; Part II. Motion Planning: 3. Geometric representations and transformations; 4. The configuration space; 5. Sampling-based motion planning; 6. Combinatorial motion planning; 7. Extensions of basic motion planning; 8. Feedback motion planning; Part III. Decision-Theoretic Planning: 9. Basic decision theory; 10. Sequential decision theory; 11. Information spaces; 12. Planning under sensing uncertainty; Part IV. Planning Under Differential Constraints: 13. Differential models; 14. Sampling-based planning under differential constraints; 15. System theory and analytical techniques.

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Book SynopsisA hands-on 2007 introductory guide to CALPHAD, the reader can directly apply the methods in the book to their own research. Several case studies put the methods into a practical context. Suitable for advanced materials design and engineering courses and to those using thermodynamic data in their research or simulations.Trade Review"Lukas (U. Stuttgart emeritus) and co-authors Sundman (Paul Sabatier U.) and independent scientist Fries provide the first introductory guide to this method of computation that combines data from thermodynamics, phase diagrams, and atomistic properties such as magnetism into a unified and consistent model. They introduce the science and art of computational thermodynamics and the past and present of the Calphad technique, the scientific basis of the technique (including thermodynamics, crystallography, equilibrium calculations and optimization methods), first principles and thermodynamic properties, experimental data needed for optimization, models for the Gibbs energy element, assessment methodology, optimization tools, and thermodynamic databases. They also offer a series of case studies, including a complete assessment of the Cu-Mg system and a complete binary system (Ca-Ng) and provide a list of websites along with comprehensive references." --Book NewsTable of ContentsPreface; 1. Introduction; 2. Basis; 3. First principles and thermodynamic properties; 4. Experimental data used for the optimisation; 5. Models for the Gibbs energy; 6. Assessment methodology; 7. Optimisation tools; 8. Creating thermodynamic databases; 9. Case studies; Bibliography; Index.

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Book SynopsisA conceptual introduction to the study of the intrinsic complexity of computational tasks. It will serve advanced undergraduate and graduate students, either as a textbook or for self-study. It provides explanations of the various sub-areas of complexity theory such as hardness amplification, pseudorandomness, and probabilistic proof systems.Trade Review"This interesting book... is refreshing to read his [Goldreichs'] opinions... The very strong focus on conceptual issues makes the book indispensible as a reference volume for research libraries." M. Bona, University of Florida, CHOICE"This book provides very well developed material that should interest advanced students either studying or doing new work on computational complexity. It would also be a valuable text for professionals challenged with solving "hard" computing problems of intending to exploit these types of problems when designing of new types computing systems." Brian A. Lawler, Software Engineering Notes"The book offers a conceptual perspective on several sub-areas of complexity theory and is intended to be used as a textbook for students and educators as well as for experts who seek an overview of of several sub-areas." Gerhard Lischke, Mathematical ReviewsTable of Contents1. Introduction and preliminaries; 2. P, NP and NP-completeness; 3. Variations on P and NP; 4. More resources, more power?; 5. Space complexity; 6. Randomness and counting; 7. The bright side of hardness; 8. Pseudorandom generators; 9. Probabilistic proof systems; 10. Relaxing the requirements; Epilogue; Appendix A. Glossary of complexity classes; Appendix B. On the quest for lower bounds; Appendix C. On the foundations of modern cryptography; Appendix D. Probabilistic preliminaries and advanced topics in randomization; Appendix E. Explicit constructions; Appendix F. Some omitted proofs; Appendix G. Some computational problems.

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Book SynopsisBased on a lecture course given at Chalmers University of Technology, this 2002 book is ideal for advanced undergraduate or beginning graduate students. The author first develops the necessary background in probability theory and Markov chains before applying it to study a range of randomized algorithms with important applications in optimization and other problems in computing. Amongst the algorithms covered are the Markov chain Monte Carlo method, simulated annealing, and the recent Propp-Wilson algorithm. This book will appeal not only to mathematicians, but also to students of statistics and computer science. The subject matter is introduced in a clear and concise fashion and the numerous exercises included will help students to deepen their understanding.Trade Review'Has climbing up onto the MCMC juggernaut seemed to require just too much effort? This delightful little monograph provides an effortless way in. The chapters are bite-sized with helpful, do-able exercises (by virtue of strategically placed hints) that complement the text.' Publication of the International Statistical Institute'… a very nice introduction to the modern theory of Markov chain simulation algorithms.' R. E. Maiboroda, Zentralblatt MATH' … extremely elegant. I am sure that students will find great pleasure in using the book - and that teachers will have the same pleasure in using it to prepare a course on the subject.' Mathematics of Computation'This elegant little book is a beautiful introduction to the theory of simulation algorithms, using (discrete) Markov chains (on finite state spaces) … highly recommended to anyone interested in the theory of Markov chain simulation algorithms.' Nieuw Archief voor WiskundeTable of Contents1. Basics of probability theory; 2. Markov chains; 3. Computer simulation of Markov chains; 4. Irreducible and aperiodic Markov chains; 5. Stationary distributions; 6. Reversible Markov chains; 7. Markov chain Monte Carlo; 8. Fast convergence of MCMC algorithms; 9. Approximate counting; 10. Propp-Wilson algorithm; 11. Sandwiching; 12. Propp-Wilson with read once randomness; 13. Simulated annealing; 14. Further reading.

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Book SynopsisThe definitive treatment of analytic combinatorics. This self-contained text covers the mathematics underlying the analysis of discrete structures, with thorough treatment of a large number of applications. Exercises, examples, appendices and notes aid understanding: ideal for individual self-study or for advanced undergraduate or graduate courses.Trade Review'… thorough and self-contained … presentation of … topics is very well organised … provides an ample amount of examples and illustrations, as well as a comprehensive bibliography. It is valuable both as a reference work for researchers working in the field and as an accessible introduction suitable for students at an advanced graduate level.' EMS NewsletterTable of ContentsPreface; An invitation to analytic combinatorics; Part A. Symbolic Methods: 1. Combinatorial structures and ordinary generating functions; 2. Labelled structures and exponential generating functions; 3. Combinatorial parameters and multivariate generating functions; Part B. Complex Asymptotics: 4. Complex analysis, rational and meromorphic asymptotics; 5. Applications of rational and meromorphic asymptotics; 6. Singularity analysis of generating functions; 7. Applications of singularity analysis; 8. Saddle-Point asymptotics; Part C. Random Structures: 9. Multivariate asymptotics and limit laws; Part D. Appendices: Appendix A. Auxiliary elementary notions; Appendix B. Basic complex analysis; Appendix C. Concepts of probability theory; Bibliography; Index.

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Book SynopsisTrade Review"Avi Wigderson, Co-Winner of the Abel Prize, Norwegian Academy of Science and Letters""Avi Wigderson's new 440-page book, Mathematics and Computation: A Theory Revolutionizing Technology and Science (Princeton University Press, October 2019), lays out a commanding overview of the theory of computing and argues for its central role in human thought."---Allyn Jackson, Communications of the ACM"This must-read book provides a high-level, enjoyable overview of numerous parts of mathematics that are related to computation in general, and computational complexity in particular." * Choice *

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Book SynopsisIntroduces the basic concepts and characteristics of string pattern matching strategies and provides numerous references for further reading. The text describes and evaluates the BF, KMP, BM, and KR algorithms, discusses improvements for string pattern matching machines, and details a technique for detecting and removing the redundant operation of the AC machine. Also explored are typical problems in approximate string matching. In addition, the reader will find a description for applying string pattern matching algorithms to multidimensional matching problems, an investigation of numerous hardware-based solutions for pattern matching, and an examination of hardware approaches for full text search.

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Book SynopsisAlgorithmic number theory is a branch of number theory, which, in addition to its mathematical importance, has substantial applications in computer science and cryptography. This book describes the various algorithms used in cryptography.Table of ContentsPrimality testing and construction of large primes Factorization of integers with exponential complexity Factorization of integers with subexponential complexity Application of elliptic curves to primality testing and factorization of integers Algorithms for computing discrete logarithm Factorization of polynomials over finite fields Reduced lattice bases and their applications Factorization of polynomials over the field of rational numbers with polynomial complexity Discrete Fourier transform and its applications High-precision integer arithmetic Solving systems of linear equations over finite fields Facts from number theory Bibliography Index.

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Book Synopsisshowing that the study of programming languages does not consist of studying languages one after another, but is organized around the features that are present in these various languages.Trade ReviewFrom the reviews:“The book is divided into eight chapters and an epilogue. … Faculty teaching an undergraduate programming languages course may find this book to be a useful reference. Summing Up: Recommended. Upper-division undergraduates through professionals/practitioners.” (J. Beidler, Choice, Vol. 48 (10), June, 2011)“It is a short book--of about 100 pages--consisting of eight chapters and an epilogue. The book focuses on the formal description of programming language semantics and compilation using denotational semantics, small-step operational semantics (reduction semantics), and big-step operational semantics (natural semantics). … The book provides a good description of programming language concepts and motivates the necessary theory well. … The book is suitable for both professionals and graduate- and advanced undergraduate-level classes.” (Michael Oudshoorn, ACM Computing Reviews, November, 2011)Table of Contents1. Terms and Relations.- 2. The Language PCF.- 3. From Evaluation to Interpretation.- 4. Compilation.- 5. PCF with Types.- 6. Type Inference.- 7. References and Assignment.- 8. Records and Objects.- 9. Epilogue.- 10. Index.- 11. Bibliography

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Book SynopsisThis is the first self-contained introduction to the use of string diagrams to reason in elementary category theory. Written in an informal expository style, it features hundreds of carefully chosen diagrams to aid understanding. With numerous worked examples and exercises, the text is ideal for graduate students and advanced undergraduates.Trade Review'String diagrams have proven an indispensable tool in modern category theory, enabling intuitive graphical reasoning while doing away with much of the bookkeeping that tends to bog down equational arguments. This textbook introduces category theory by way of string diagrams, making it an excellent choice both for beginners in category theory, as well as for more experienced category theorists seeking to add string diagrammatic reasoning to their repertoire.' Robin Kaarsgaard, University of Edinburgh'Well-chosen notation plays a vital role in constructive calculation because it facilitates the exploitation of algebraic properties. This book's exemplary use of string diagrams in category theory will inspire and invigorate the calculational method. Peruse and ponder its colourful beauty.' Roland Backhouse, University of NottinghamTable of ContentsPrologue; 1. Category theory; 2. String diagrams; 3. Monads; 4. Adjunctions; 5. Putting it all together; Epilogue; Appendix. Notation; References; Index.

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Book SynopsisOccultism and the Origins of Psychoanalysis traces the origins of key psychoanalytic ideas back to their roots in hypnosis and the occult. Maria Pierri follows Freud’s early interest in ‘thought-transmission’, now known as telepathy. Trade Review"This book gives back to contemporary psychoanalysis the pleasure of exploring really little-known territories, fascinatingly restoring the connection between the past, present and "elsewhere" of communications between human beings, using the Freudian experience as its starting point, in order to reconsider in a reflective way the less visible, sometimes disorienting and mysterious levels of psychoanalytic practice. offers us an especially valuable reflection on the mysterious communicating paths which put individual and group unconsciouses in contact with each other, often bypassing in an apparently disconcerting manner the border controls." - Stefano Bolognini, past President of the IPA and the Italian Psychoanalytic Society"Following the thread of thought-transference, Maria Pierri goes through the events of the Freudian endeavour starting from its roots in hypnosis and occultism, through the dialogue with the masters, the pupils and the great female patients, the leading actresses of the cure. In his disquieting curiosity for telepathy, which he shared intimately with Ferenczi, Freud discovers that fortune-tellers, who do not know the future, can read the unconscious of their clients. But the "golden coin" of occultism, the generative mother-child communication, will be the great discovery of Ferenczi." - Luis J. Martin Cabré, Training analyst, past President Madrid Psychoanalytical Association."Today we know much about the polyphonic complex of contexts, experiences, relationships and ideas which made psychoanalysis possible and still nourish its current debates. We can be very grateful to Maria Pierri for bringing us up to date with the role and meaning of some little-known aspects of Freud’s life and work concerning occultism and the fascinating dialogue of the unconsciouses developed with Ferenczi: what the Author identifies as one of the matrices of the developments of contemporary psychoanalysis." - Marco Conci, MC, IPA Committee on the History of Psychoanalysis"This book gives back to contemporary psychoanalysis the pleasure of exploring really little-known territories, fascinatingly restoring the connection between the past, present and 'elsewhere' of communications between human beings, using the Freudian experience as its starting point, in order to reconsider in a reflective way the less visible, sometimes disorienting and mysterious levels of psychoanalytic practice. It offers us an especially valuable reflection on the mysterious communicating paths which put individual and group unconsciouses in contact with each other, often bypassing in an apparently disconcerting manner the border controls." - Stefano Bolognini, past president of the IPA and the Italian Psychoanalytic Society"Following the thread of thought-transference, Maria Pierri goes through the events of the Freudian endeavour starting from its roots in hypnosis and occultism, through the dialogue with the masters, the pupils and the great female patients, the leading actresses of the cure. In his disquieting curiosity for telepathy, which he shared intimately with Ferenczi, Freud discovers that fortune-tellers, who do not know the future, can read the unconscious of their clients. But the 'golden coin' of occultism, the generative mother-child communication, will be the great discovery of Ferenczi." - Luis J. Martin Cabré, training analyst, past president, Madrid Psychoanalytical Association"Today we know much about the polyphonic complex of contexts, experiences, relationships and ideas which made psychoanalysis possible and still nourish its current debates. We can be very grateful to Maria Pierri for bringing us up to date with the role and meaning of some little-known aspects of Freud’s life and work concerning occultism and the fascinating dialogue of the unconsciouses developed with Ferenczi: what the Author identifies as one of the matrices of the developments of contemporary psychoanalysis." - Marco Conci, MC, IPA Committee on the History of PsychoanalysisTable of ContentsIntroductionStefano BologniniPrologue: a result of character: the cocaine, this magical substance1. Vienna, Porta Orientis of the Unconscious The force of suggestion: the "wonderful somnambulists" HypnosisVienna, laboratory of modernity2. The Young FreudA passionate young researcher into natureFirst love Martha and Bertha: the languages of passion3. The Lesson of Jean Martin Charcot At the SalpêtrièreThe apparatus of language The magic of words4. The lesson of Josef Breuer and the "descent to the mothers"Studies on hysteriaA difficult separation: not all debts can be paidA foundation myth: a false pregnancy and a cure with a defect.5. Sigmund Freud’s lessonThe discovery of a false connection Irma’s throat and the feminine at the origin of psychoanalysis.Dream as desire 6. Fliess and the invention of psychoanalysis A secret correspondence My friend in BerlinFreud’s heart trouble7. The discovery of infantile sexualitySelf-analysis and the writing cure Cherchez la femme: the case of Emma Eckstein8. Original thought requires a ruptureThe "reader of thoughts" The accusation of plagiarism A future in the image of the past: predestination and superstition 9. Occultism made in the USASpiritualism Medium, media, and "mental telegraphy"First hypotheses about the unconscious10 Jung, spiritualism, and countertransference: the world of the deadJung, Poltergeist phenomena, and séances The arrival at Burghölzli First visit to ViennaEaster 1909: Jung’s spiritual complex and Sabina The dangerous fascination of the "beautiful Jewess"11. Ferenczi, the unclassifiableThe sultan and his "clairvoyant" A psychoanalyst "of a restless mind"Ferenczi and the hidden treasure of SpiritualismThe encounter with Freud: a postponed transferential appointment12. A journey to America Three men and an eventful, mutually analytic crossing: the outward journey… … and back again13. The Danaan gift The clairvoyant who reads Ferenczi’s mindThe patient who reads Ferenczi’s mindThe Palermo incident, or the interpretation of paranoiaThe psychic work of the clairvoyant: two unfulfilled prophecies14. An epistolary novelFerenczi and incestuous countertransferential storms: from mother to daughter What is still missing is the fatherly blessing: fatefulness and Oedipal coincidencesElma Pàlos, fragment of the analysis of a seduction The open wound in Ferenczi’s heart, a source of creativity 15. The Saturday goy: getting to know Dr Jones The Welsh liar Difficult beginnings Freud’s first pupil from BritainDr Jones’s stethoscope: rationalisation and censorship of excess countertransferenceA prescribed training analysis in Budapest 16. The intergenerational transmission of psychoanalysis Love and death: the three women of the three pupils"If you go to women, don't forget the whip"At school with Freud: the transmission of psychoanalysis17. The secret committeeThe transformations and the desertion of JungA missed meeting: the "Kreuzlingen gesture" The Committee: the Männerbund and the defence of the "Cause" (Die Sache)Totem and taboo: unconscious intelligence and intergenerational transmission of thought 18. 1913 - the year before the warThe last congress with JungA black tide of occultism The question of telepathyThe dialogues of the unconsciousEpilogue: a fortune-teller visits Freud in BerggasseCorrespondenceIndex

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Book SynopsisComputational Framework for the Finite Element Method in MATLAB and Python aims to provide a programming framework for coding linear FEM using matrix-based MATLAB language and Python scripting language. It describes FEM algorithm implementation in the most generic formulation so that it is possible to apply this algorithm to as many application problems as possible. Readers can follow the step-by-step process of developing algorithms with clear explanations of its underlying mathematics and how to put it into MATLAB and Python code. The content is focused on aspects of numerical methods and coding FEM rather than FEM mathematical analysis. However, basic mathematical formulations for numerical techniques which are needed to implement FEM are provided. Particular attention is paid to an efficient programming style using sparse matrices. Features Contains ready-to-use coding recipes allowing fast prototyping and

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Book SynopsisHandbook of Price Impact Modeling provides practitioners and students with a mathematical framework grounded in academic references to apply price impact models to quantitative trading and portfolio management. Automated trading is now the dominant form of trading across all frequencies. Furthermore, trading algorithm rise introduces new questions professionals must answer, for instance: How do stock prices react to a trading strategy? How to scale a portfolio considering its trading costs and liquidity risk? How to measure and improve trading algorithms while avoiding biases? Price impact models answer these novel questions at the forefront of quantitative finance. Hence, practitioners and students can use this Handbook as a comprehensive, modern view of systematic trading.For financial institutions, the Handbookâs framework aims to minimize the firmâs price impact, measure market liquiditTrade Review"Kevin Webster has written a remarkable textbook that studies these problems in a uniquely comprehensive manner. To wit, he covers theory, empirics, and implementation by bringing together insights developed in a number of different research communities, ranging from Industry Practitioners, Financial Economists, Econophysicists, to Applied Mathematicians. In doing so, Kevin develops the underlying theory in a very accessible manner. He also presents important practical applications beyond optimal trading (such as risk management), which showcase that a good grasp of the mechanics of price impact is an essential part of any modern financial engineer's toolkit."- Johannes Muhle-Karbe, Imperial College London.Full article: Handbook of Price Impact Modeling (tandfonline.com)Table of Contents1. Introduction to Modeling Price Impact. 2. Mathematical Models of Price Impact. 3. Applications of Price Impact Models. 4. Further Applications of Price Impact Models. 5. An Introduction to the Mathematics of Causal Inference. 6. Dealing with Biases when Fitting Price Impact Models. 7. Empirical Analysis of Price Impact Models.

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