Mathematical theory of computation Books

Book SynopsisThese lecture notes provide a systematic introduction to matrix models of quantum field theories with non-commutative and fuzzy geometries. The book initially focuses on the matrix formulation of non-commutative and fuzzy spaces, followed by a description of the non-perturbative treatment of the corresponding field theories. As an example, the phase structure of non-commutative phi-four theory is treated in great detail, with a separate chapter on the multitrace approach. The last chapter offers a general introduction to non-commutative gauge theories, while two appendices round out the text. Primarily written as a self-study guide for postgraduate students – with the aim of pedagogically introducing them to key analytical and numerical tools, as well as useful physical models in applications – these lecture notes will also benefit experienced researchers by providing a reference guide to the fundamentals of non-commutative field theory with an emphasis on matrix models and fuzzy geometries.Trade Review“The book collects almost all that has been achieved on the topic within the recent years, including all major results of many authors. As such, it is a nice reference work for graduate students and beginning researchers who want to pursue research in this area. Having all the results and different approaches collected in one place, together with the exhaustive list of references make this a valuable compendium to everyone working on noncommutative models of quantum field theory.” (Andrzej Sitarz, zbMATH 1371.81013, 2017)Table of ContentsPreface.- Introductory Remarks.- The Non-Commutative Moyal-Weyl Spaces Rd.- The Fuzzy Sphere.- Quantum Non-Commutative Phi-Four.- The Multitrace Approach.- Non-Commutative Gauge Theory.- Appendix A - The Landau States.- Appendix B - The Traces TrtAtB and TrtAtBtCtD.- Index.

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Book SynopsisBiggs'' Discrete Mathematics has been a best-selling textbook since the first and revised editions were published in 1986 and 1990, respectively. This second edition has been developed in response to undergraduate course changes and changes in students'' needs. New to this edition are chapters on statements and proof, logical framework, and natural numbers and the integers, in addition to updated chapters from the previous edition. The new chapters are presented at a level suitable for mathematics and computer science students seeking a first approach to this broad and highly relevant topic. Each chapter contains newly developed tailored exercises, and miscellaneous exercises are presented throughout, providing the student with over 1000 individual tailored exercises. This edition is accompanied by a website www.oup.com/mathematics/discretemath containing hints and solutions to all exercises presented in the text, providing an invaluable resource for students and lecturers alike. The bTrade ReviewThis is a new edition of a successful textbook ... this revision is particularly welcome ... The text is written in a fluent but rigorous style and should appeal to sixthformers and undergraduates who are alienated by more formal presentations. There are plenty of approachable exercises, ranging from easy riders to establish technique to more challenging problems which introduce new ideas, and a bonus is that all the answers are available on a companion web-site. I can thoroughly recommend this text. * The Mathematical Gazette *A well known definition says that a textbook is a book such that everybody thinks he can write a better one. Biggs' Discrete Mathematics is an exception - not only for its wide range of topics and its clear organization but notably for its excellent style of explanation. * EMS *... the ideal choice for introductory courses to discrete mathematicians. * Zentralblatt MATH *Table of ContentsTHE LANGUAGE OF MATHEMATICS; TECHNIQUES; ALGORITHMS AND GRAPHS; ALGEBRAIC METHODS

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Book SynopsisArguably the strongest addition to numerical finance of the past decade, Algorithmic Adjoint Differentiation (AAD) is the technology implemented in modern financial software to produce thousands of accurate risk sensitivities, within seconds, on light hardware.AAD recently became a centerpiece of modern financial systems and a key skill for all quantitative analysts, developers, risk professionals or anyone involved with derivatives. It is increasingly taught in Masters and PhD programs in finance.Danske Bank''s wide scale implementation of AAD in its production and regulatory systems won the In-House System of the Year 2015 Risk award. The Modern Computational Finance books, written by three of the very people who designed Danske Bank''s systems, offer a unique insight into the modern implementation of financial models. The volumes combine financial modelling, mathematics and programming to resolve real life financial problems and produce effective derivatives Table of ContentsModern Computational Finance xi Preface by Leif Andersen xv Acknowledgments xix Introduction xxi About the Companion C++ Code xxv PART I Modern Parallel Programming 1 Introduction 3 CHAPTER 1 Effective C++ 17 CHAPTER 2 Modern C++ 25 2.1 Lambda expressions 25 2.2 Functional programming in C++ 28 2.3 Move semantics 34 2.4 Smart pointers 41 CHAPTER 3 Parallel C++ 47 3.1 Multi-threaded Hello World 49 3.2 Thread management 50 3.3 Data sharing 55 3.4 Thread local storage 56 3.5 False sharing 57 3.6 Race conditions and data races 62 3.7 Locks 64 3.8 Spinlocks 66 3.9 Deadlocks 67 3.10 RAII locks 68 3.11 Lock-free concurrent design 70 3.12 Introduction to concurrent data structures 72 3.13 Condition variables 74 3.14 Advanced synchronization 80 3.15 Lazy initialization 83 3.16 Atomic types 86 3.17 Task management 89 3.18 Thread pools 96 3.19 Using the thread pool 108 3.20 Debugging and optimizing parallel programs 113 PART II Parallel Simulation 123 Introduction 125 CHAPTER 4 Asset Pricing 127 4.1 Financial products 127 4.2 The Arbitrage Pricing Theory 140 4.3 Financial models 151 CHAPTER 5 Monte-Carlo 185 5.1 The Monte-Carlo algorithm 185 5.2 Simulation of dynamic models 192 5.3 Random numbers 200 5.4 Better random numbers 202 CHAPTER 6Serial Implementation 213 6.1 The template simulation algorithm 213 6.2 Random number generators 223 6.3 Concrete products 230 6.4 Concrete models 245 6.5 User interface 263 6.6 Results 268 CHAPTER 7 Parallel Implementation 271 7.1 Parallel code and skip ahead 271 7.2 Skip ahead with mrg32k3a 276 7.3 Skip ahead with Sobol 282 7.4 Results 283 PART III Constant Time Differentiation 285 Introduction 287 CHAPTER 8 Manual Adjoint Differentiation 295 8.1 Introduction to Adjoint Differentiation 295 8.2 Adjoint Differentiation by hand 308 8.3 Applications in machine learning and finance 315 CHAPTER 9 Algorithmic Adjoint Differentiation 321 9.1 Calculation graphs 322 9.2 Building and applying DAGs 328 9.3 Adjoint mathematics 340 9.4 Adjoint accumulation and DAG traversal 344 9.5 Working with tapes 349 CHAPTER 10 Effective AAD and Memory Management 357 10.1 The Node class 359 10.2 Memory management and the Tape class 362 10.3 The Number class 379 10.4 Basic instrumentation 398 CHAPTER 11 Discussion and Limitations 401 11.1 Inputs and outputs 401 11.2 Higher-order derivatives 402 11.3 Control flow 402 11.4 Memory 403 CHAPTER 12 Differentiation of the Simulation Library 407 12.1 Active code 407 12.2 Serial code 409 12.3 User interface 417 12.4 Serial results 424 12.5 Parallel code 426 12.6 Parallel results 433 CHAPTER 13 Check-Pointing and Calibration 439 13.1 Check-pointing 439 13.2 Explicit calibration 448 13.3 Implicit calibration 475 CHAPTER 14 Multiple Differentiation in Almost Constant Time 483 14.1 Multidimensional differentiation 483 14.2 Traditional Multidimensional AAD 484 14.3 Multidimensional adjoints 485 14.4 AAD library support 487 14.5 Instrumentation of simulation algorithms 494 14.6 Results 499 CHAPTER 15 Acceleration with Expression Templates 503 15.1 Expression nodes 504 15.2 Expression templates 507 15.3 Expression templated AAD code 524 Debugging AAD Instrumentation 541 Conclusion 547 References 549 Index 555

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Book SynopsisKeeping students involved and actively learning is challenging. Instructors in computer science are aware of the cognitive value of modelling puzzles and often use logical puzzles as an efficient pedagogical instrument to engage students and develop problem-solving skills. This unique book is a comprehensive resource that offers teachers and students fun activities to teach and learn logic. It provides new, complete, and running formalisation in Propositional and First Order Logic for over 130 logical puzzles, including Sudoku-like puzzles, zebra-like puzzles, island of truth, lady and tigers, grid puzzles, strange numbers, or self-reference puzzles. Solving puzzles with theorem provers can be an effective cognitive incentive to motivate students to learn logic. They will find a ready-to-use format which illustrates how to model each puzzle, provides running implementations, and explains each solution. This concise and easy-to-follow textbook is a much-needed support tool for students willing to explore beyond the introductory level of learning logic and lecturers looking for examples to heighten student engagement in their computer science courses. Trade Review“The purpose of this book is to introduce first-order logic (FOL) to newcomers. … The book is a treasure trove of puzzles like this. … All of these are motivated in an approachable, fun way. … the book is a hands-on guide to Prover9 and Mace4 … . It is quite valuable to have so many puzzles in a single book.” (Jesse Adam Alama, Mathematical Reviews, October, 2022)Table of ContentsPreface.- Getting Started with Prover9 and Mace4.- Micro Arithmetic Puzzles.- Strange Numbers.- Practical Puzzles.- Lady and Tigers.- Einstein Puzzles.- Island of Truth.- Love and Marriage.- Grid Puzzles.- Japanese Puzzles.- Russian Puzzles.- Polyomino Puzzles.- Self-reference and Other Puzzles.- Epigraph in Natural Language

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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 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 SynopsisThis book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former and enjoying the robustness and elegance of the latter.This book can be used in a graduate course in deep learning, with the first few parts being accessible to senior undergraduates. In addition, the book will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject. Trade Review“This book is useful to students who have already had an introductory course in machine learning and are further interested to deepen their understanding of the machine learning material from the mathematical point of view.” (T. C. Mohan, zbMATH 1441.68001, 2020)Table of ContentsIntroductory Problems.- Activation Functions.- Cost Functions.- Finding Minima Algorithms.- Abstract Neurons.- Neural Networks.- Approximation Theorems.- Learning with One-dimensional Inputs.- Universal Approximators.- Exact Learning.- Information Representation.- Information Capacity Assessment.- Output Manifolds.- Neuromanifolds.- Pooling.- Convolutional Networks.- Recurrent Neural Networks.- Classification.- Generative Models.- Stochastic Networks.- Hints and Solutions.

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Book SynopsisThis book celebrates the work of Don Pigozzi on the occasion of his 80th birthday. In addition to articles written by leading specialists and his disciples, it presents Pigozzi’s scientific output and discusses his impact on the development of science. The book both catalogues his works and offers an extensive profile of Pigozzi as a person, sketching the most important events, not only related to his scientific activity, but also from his personal life. It reflects Pigozzi's contribution to the rise and development of areas such as abstract algebraic logic (AAL), universal algebra and computer science, and introduces new scientific results. Some of the papers also present chronologically ordered facts relating to the development of the disciplines he contributed to, especially abstract algebraic logic. The book offers valuable source material for historians of science, especially those interested in history of mathematics and logic.Table of ContentsA Mathematical Life; Pigozzi, Don.- Assertional logics, truth-equational logics, and the hierarchiesof abstract algebraic logic; Albuquerque, Hugo, Font, Josep Maria, Jansana, Ramon, and Moraschini, Tommaso.- Deduction-Detachment Theorem and Gentzen-Style Deductive Systems; Babenyshev, Sergey.- Introducing Boolean Semilattices; Bergman, Clifford.- The Equationally-Defined Commutator in Quasivarieties Generated by Two-Element Algebras; Czelakowski, Janusz.- A short overview of Hidden Logic; Ferreirim, Isabel and Martins, Manuel A.- Absorption and directed J´onsson terms; Kazda, Alexandr, Kozik, Marcin, McKenzie, Ralph and Moore, Matthew.- Relatively congruence modular quasivarieties of modules; Kearnes, Keith A. - The computational complexity of deciding whether a finite algebra generates a minimal variety; McNulty, George F.- Characterization of protoalgebraic k-deductive systems; Palasinska; Katarzyna.- Diagrammatic duality; Romanowska, Anna B. and Smith, Jonathan D.H.- Boolean product representations of algebras via binary polynomials; Salibra, Antonino, Ledda, Antonio, and Paoli, Francesco.- Paraconsistent constructive logic with strong negation as a contraction-free relevant logic; Spinks, Matthew and Veroff, Robert.- Possible classification of finite-dimensional compact Hausdorfftopological algebras; Taylor, Walter.- Categorical Abstract Algebraic Logic: Compatibility Operators and Correspondence Theorems; Voutsadakis; George.

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Book SynopsisIntroductory courses in combinatorial optimization are popular at the upper undergraduate/graduate levels in computer science, industrial engineering, and business management/OR, owed to its wide applications in these fields. There are several published textbooks that treat this course and the authors have used many of them in their own teaching experiences. This present text fills a gap and is organized with a stress on methodology and relevant content, providing a step-by-step approach for the student to become proficient in solving combinatorial optimization problems. Applications and problems are considered via recent technology developments including wireless communication, cloud computing, social networks, and machine learning, to name several, and the reader is led to the frontiers of combinatorial optimization. Each chapter presents common problems, such as minimum spanning tree, shortest path, maximum matching, network flow, set-cover, as well as key algorithms, such as greedy algorithm, dynamic programming, augmenting path, and divide-and-conquer. Historical notes, ample exercises in every chapter, strategically placed graphics, and an extensive bibliography are amongst the gems of this textbook.Trade Review“This book introduces combinatorial optimization with a methodology-oriented organization. It targets undergraduate and graduate students and contains a good mix of theoretical results (with proof) and examples, which helps the reader acquire ideas and concepts. The chapters end with a list of exercises for the students.” (Francisco Chicano, Mathematical Reviews, January, 2024)“The book can appropriately be used as a textbook in a graduate course. All the algorithms are clearly explained and presented. It is a very valuable book for successful application of real problems from combinatorial optimization. … this book is an excellent contribution to the field of combinatorial optimization, and it is highly recommended to the students and researchers in optimization.” (Samir Kumar Neogy, zbMATH 1512.90001, 2023)Table of Contents1. Introduction.-2. Divide-and-Conquer.- 3. Dynamic Programming and Shortest Path.- 4. Greedy Algorithm and Spanning Tree.- 5. Incremental Method and Maximum Network Flow.- 6. Linear Programming.- 7. Primal-Dual Methods and Minimum Cost Flow.- 8. NP-hard Problems and Approximation Algorithms.- 9. Restriction and Steiner Tree.- 10. Greedy Approximation and Submodular Optimization.- 11. Relaxation and Rounding. 12. Nonsubmodular Optimization.- 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 SynopsisPython's simplicity and versatility make it an ideal language for both beginners and experienced programmers. Its syntax facilitates a smooth learning curve, enabling individuals to concentrate on grasping programming concepts instead of wrestling with intricate syntax rules. The extensive standard library reinforces its practicality, offering pre-built modules and functions that reduce manual coding efforts. Python's versatility is evident in its applications, spanning web development, data analysis, Machine Learning and automation.The language's interactive nature supports real-time code experimentation, stepping up the learning process and enhancing understanding. Python's wealth of online resources further enriches the learning experience, fostering a community where individuals can develop their programming skills. Python: A Practical Learning Approach exemplifies Python's simplicity and versatility with numerous examples, ensuring a seamless learning journ

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Book SynopsisUsing basic category theory, this Element describes all the central concepts and proves the main theorems of theoretical computer science. Category theory, which works with functions, processes, and structures, is uniquely qualified to present the fundamental results of theoretical computer science. In this Element, readers will meet some of the deepest ideas and theorems of modern computers and mathematics, such as Turing machines, unsolvable problems, the P=NP question, Kurt Gödel''s incompleteness theorem, intractable problems, cryptographic protocols, Alan Turing''s Halting problem, and much more. The concepts come alive with many examples and exercises.Table of Contents1. Introduction; 2. Aide-Mémoire for Category Theory; 3. Models of Computation; 4. Computability Theory; 5. Complexity Theory; 6. Diagonal Arguments; 7. Conclusion; References.

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Book SynopsisThis book introduces the fundamentals of the theory of quantum computing, illustrated with code samples written in Q#, a quantum-specific programming language, and its related Quantum Development Kit. Quantum computing (QC) is a multidisciplinary field that sits at the intersection of quantum physics, quantum information theory, computer science and mathematics, and which may revolutionize the world of computing and software engineering. The book begins by covering historical aspects of quantum theory and quantum computing, as well as offers a gentle, algebra-based, introduction to quantum mechanics, specifically focusing on concepts essential for the field of quantum programming. Quantum state description, state evolution, quantum measurement and the Bell’s theorem are among the topics covered. The readers also get a tour of the features of Q# and familiarize themselves with the QDK. Next, the core QC topics are discussed, complete with the necessary mathematical formalism. This includes the notions of qubit, quantum gates and quantum circuits. In addition to that, the book provides a detailed treatment of a series of important concepts from quantum information theory, in particular entanglement and the no-cloning theorem, followed by discussion about quantum key distribution and its various protocols. Finally, the canon of most important QC algorithms and algorithmic techniques is covered in-depth - from the Deutsch-Jozsa algorithm, through Grover’s search, to Quantum Fourier Transform, quantum phase estimation and Shor’s algorithm. The book is an accessible introduction into the vibrant and fascinating field of quantum computing, offering a blend of academic diligence with pragmatism that is so central to software development world. All of the discussed theoretical aspects of QC are accompanied by runnable code examples, providing the reader with two different angles - mathematical and programmatic - of looking at the same problem space. Table of ContentsPart One1 Background 1.1 Historical development of quantum theory 1.2 Reality without realism 2 Basics of quantum mechanics 2.1 Quantum state 2.2 Superposition 2.3 Born rule 2.4 Observables 2.5 State evolution 2.6 Larger systems 2.7 Postulates of quantum mechanics 2.8 Entanglement 2.9 Bell’s theorem 2.10 No-cloning theorem Part Two 3 Getting Started with Quantum Programming 3.1 Setting up QDK environment 3.2 Getting started with Q# 4 Quantum Computing 4.1 History 4.2 Qubits 4.3 Quantum circuits 4.4 Superposition 4.5 Pauli gates 4.5.1 I gate 4.5.2 X gate 4.5.3 Z gate 4.5.4 Y gate 4.5.5 Summary 4.6 Rotation gates 4.6.1 Rz gate 4.6.2 S gate 4.6.3 T gate 4.6.4 Rx and Ry gates 4.7 Multi qubit gates 4.7.1 Controlled gates 4.7.2 CNOT gate 4.7.3 SWAP gate 4.7.4 CZ gate 4.7.5 Toffoli gate 4.8 Gate universality 5 Entanglement 5.1 Basics 5.2 Bell’s inequalities 5.3 CHSH Game 5.4 Teleportation 5.5 Superdense coding 5.6 Entanglement as a resource 6 Quantum Key Distribution 6.1 One-time pad encryption 6.2 BB84 protocol 6.3 B92 protocol 6.4 EPR-based quantum key distribution Part Three 7 Algorithms 7.1 Deutsch-Jozsa Algorithm 7.2 QuantumSearch 7.3 Useful Algorithm Components 7.3.1 QFT 7.3.2 QPE 7.4 Shor’s Algorithm

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Book SynopsisThis textbook is a thorough, up-to-date introduction to the principles and techniques that guide the design and implementation of modern programming languages. The goal of the book is to provide the basis for a critical understanding of most modern programming languages. Thus, rather than focusing on a specific language, the book identifies the most important principles shared by large classes of languages. The notion of ‘abstract machine’ is a unifying concept that helps to maintain an accurate and elementary treatment. The book introduces, analyses in depth, and compares the imperative, object-oriented, functional, logic, concurrent, constraint-based, and service-oriented programming paradigms. All material coming from the first English edition has been updated and extended, clarifying some tricky points, and discussing newer programming languages. This second edition contains new chapters dedicated to constraint, concurrent, and service-oriented programming.Topics and features: Requires familiarity with one programming language is a prerequisite Provides a chapter on history offering context for most of the constructs in use today Presents an elementary account of semantical approaches and of computability Introduces new examples in modern programming languages like Python or Scala Offers a chapter that opens a perspective on applications in artificial intelligence Conceived as a university textbook, this unique volume will also be suitable for IT specialists who want to deepen their knowledge of the mechanisms behind the languages they use. The choice of themes and the presentation style are largely influenced by the experience of teaching the content as part of a bachelor's degree in computer science.Table of Contents1. Abstract Machines.- 2. How to Describe a Programming Language.- 3. Foundations.- 4. Names and the Environment.- 5. Memory Management.- 6. Control Structure.- 7. Control Abstraction.- Structuring Data.- 8. Data Abstraction.- 9. The Object-Oriented Paradigm.- 10. The Functional Paradigm.- 11. The Logic Programming Paradigm.- 12. A Short Historical Perspective.

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Book SynopsisThis introduction to computational geometry focuses on algorithms. Motivation is provided from the application areas as all techniques are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement.Trade Review"An excellent introduction to the field is given here, including a general motivation and usage cases beyond simple graphics rendering or interaction." from the ACM Reviews by William Fahle, University of Texas at Dallas, USATable of ContentsComputational Geometry: Introduction.- Line Segment Intersection: Thematic Map Overlay.- Polygon Triangulation: Guarding an Art Gallery.- Linear Programming: Manufacturing with Molds.- Orthogonal Range Searching: Querying a Database.- Point Location: Knowing Where You Are.- Voronoi Diagrams: The Post Office Problem.- Arrangements and Duality: Supersampling in Ray Tracing.- Delaunay Triangulations: Height Interpolation.- More Geometric Data Structures: Windowing.- Convex Hulls: Mixing Things.- Binary Space Partitions: The Painter's Algorithm.- Robot Motion Planning: Getting Where You Want to Be.- Quadtrees: Non-Uniform Mesh Generation.- Visibility Graphs: Finding the Shortest Route.- Simplex Range Searching: Windowing Revisited.- 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 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 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 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 SynopsisSpectral Changes of 1/F Noise in Metals at Clusterization of Light Interstitials.- Analytic Solutions of Boundary Value Problems for Model Kinetic Equations.- Mathematical Models in Non-Linear Systems Thermodynamics.- Critical OpalescenceModels: Experiment.- Methane Combustion Simulation on Multiprocessor Computer Systems.- Computer Simulation of Structural Modifications in the Metal Samples Irradiated by Pulsed Beams.- Visualisation of Grand Challenge Data on Distributed Systems.- Simulation of Electron Transport in Semiconductor Microstructures: Field Emission from Nanotip.- Reliable Computing Experiment in the Study of Generalized Controllability of Linear Functional Differential Systems.- Heat Transfer in Disperse Systems of Various Structures and Configurations.- Some New Results in the Theory of Intelligent Systems.- An Automata Approach to Analysis and Synthesis of Audio and Video Patterns.- A Mathematical Model of Controlling the Portfolio of a Commercial Bank.- Tutoring Process as Object for Situational Control.- Nonlinear Dynamics of Strongly Non-Homogeneous Chains with Symmetric Characteristics.- Models of Directed Self-Avoiding Walks and Statistics of Rigid Polymer Molecules.- Postulate of the Arithmetical Mean and Nonbonded Interactions.- Quantum-Chemical Models of the Structure and the Functions of the Active Centres of the Polynuclear Complexes.- Asymptotics of Transport Equations for Spherical Geometry in L2 with Reflecting Boundary Conditions.- Traveling Heat Waves in High Temperature Medium.- Smooth Lyapunov Manifolds and Correct Mathematical Simulation of Nonlinear Singular Problems in Mathematical Physics.- Computational Methods for the Estimation of the Aerosol Size Distributions.- Two Disperse Particles in the Field of the ElectromagneticRadiation.- Transport Processes in Aerodisperse Systems: Transitional Growth of Nonspherical Particles and Mobility of Ions.- Solution of Some Nonlinear Problems in the Theory of Heating, Vaporization, Burning of Solid Particles and Drops.- On the Irreducible Tensors Method in the Theory of Diffusive Interaction between Particles.- Evaporation and Growth of Single Drops and Finite Array of Interacting Drops of Pure Liquids and Hygroscopic Solutions.Table of Contents1. Models of Nonlinear Phenomena in Physics. 2. Numerical Methods and Computer Simulations. 3. Mathematical Computer Models of Discrete Systems. 4. Mathematical Models in Economics. 5. Nonlinear Models in Chemical Physics and Physical Chemistry. 6. Mathematical Models of Transport Processes in Complex Systems.

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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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a huge range and FREE tracked UK delivery on ALL orders.

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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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a huge range and FREE tracked UK delivery on ALL orders.

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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 SynopsisCryptography, in particular public-key cryptography, has emerged in the last 20 years as an important discipline that is not only the subject of an enormous amount of research, but provides the foundation for information security in many applications. Standards are emerging to meet the demands for cryptographic protection in most areas of data communications. Public-key cryptographic techniques are now in widespread use, especially in the financial services industry, in the public sector, and by individuals for their personal privacy, such as in electronic mail. This Handbook will serve as a valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography. It is a necessary and timely guide for professionals who practice the art of cryptography. The Handbook of Applied Cryptography provides a treatment that is multifunctional:It serves as an introduction to the more practical aspects of both conventionalTrade Review"…very well suited for the reader who wants an encyclopedic description of the state of the art of applied modern cryptography."-Mathematical Reviews, Issue 99g "[This book] is an incredible achievement. … [T]he handbook is complete. If I want to check what problems there were with a proposed system, determine how the variations on a particular algorithm developed, see what research preceded and followed an idea, I go to the Handbook. The Handbook has accurate, clear, and correct information. It is wonderful. … If I were limited to only one cryptography text on my shelves, it would be the Handbook of Applied Cryptography." - Bulletin of the AMS Table of ContentsForeword by Ronald L. Rivest Overview of Cryptography Introduction Information security and cryptography Background on functions Functions(1-1, one-way, trapdoor one-way) Permutations Involutions Basic terminology and concepts Symmetric-key encryption Overview of block ciphers and stream ciphers Substitution ciphers and transposition ciphers Composition of ciphers Stream ciphers The key space Digital signatures Authentication and identification Identification Data origin authentication Public-key cryptography Public-key encryption The necessity of authentication in public-key systems Digital signatures from reversible public-key encryption Symmetric-key versus public-key cryptography Hash functions Protocols and mechanisms Key establishment, management, and certification Key management through symmetric-key techniques Key management through public-key techniques Trusted third parties and public-key certificates Pseudorandom numbers and sequences Classes of attacks and security models Attacks on encryption schemes Attacks on protocols Models for evaluating security Perspective for computational security Notes and further references Mathematical Background Probability theory Basic definitions Conditional probability Random variables Binomial distribution Birthday attacks Random mappings Information theory Entropy Mutual information Complexity theory Basic definitions Asymptotic notation Complexity classes Randomized algorithms Number theory The integers Algorithms in Z The integers modulo n Algorithms in Zn The Legendre and Jacobi symbols Blum integers Abstract algebra Groups Rings Fields Polynomial rings Vector spaces Finite fields Basic properties The Euclidean algorithm for polynomials Arithmetic of polynomials N

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Book Synopsis

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Book SynopsisIntroduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and âœbottom up,â which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed.Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms.Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments.All the major Python libraries for science and e

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Book SynopsisPython Programming for Mathematics focuses on the practical use of the Python language in a range of different areas of mathematics. Through fifty-five exercises of increasing difficulty, the book provides an expansive overview of the power of using programming to solve complex mathematical problems.This book is intended for undergraduate and graduate students who already have learned the basics of Python programming and would like to learn how to apply that programming skill in mathematics.Features Innovative style that teaches programming skills via mathematical exercises. Ideal as a main textbook for Python for Mathematics courses, or as a supplementary resource for Numerical Analysis and Scientific Computing courses.

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Book SynopsisAccurate, robust and fast image reconstruction is a critical task in many scientific, industrial and medical applications. Over the last decade, image reconstruction has been revolutionized by the rise of compressive imaging. It has fundamentally changed the way modern image reconstruction is performed. This in-depth treatment of the subject commences with a practical introduction to compressive imaging, supplemented with examples and downloadable code, intended for readers without extensive background in the subject. Next, it introduces core topics in compressive imaging including compressed sensing, wavelets and optimization in a concise yet rigorous way, before providing a detailed treatment of the mathematics of compressive imaging. The final part is devoted to recent trends in compressive imaging: deep learning and neural networks. With an eye to the next decade of imaging research, and using both empirical and mathematical insights, it examines the potential benefits and the piTable of Contents1. Introduction; Part I. The Essentials of Compressive Imaging: 2. Images, transforms and sampling; 3. A short guide to compressive imaging; 4. Techniques for enhancing performance; Part II. Compressed Sensing, Optimization and Wavelets: 5. An introduction to conventional compressed sensing; 6. The LASSO and its cousins; 7. Optimization for compressed sensing; 8. Analysis of optimization algorithms; 9. Wavelets; 10. A taste of wavelet approximation theory; Part III. Compressed Sensing with Local Structure: 11. From global to local; 12. Local structure and nonuniform recovery; 13. Local structure and uniform recovery; 14. Infinite-dimensional compressed sensing; Part IV. Compressed Sensing for Imaging: 15. Sampling strategies for compressive imaging; 16. Recovery guarantees for wavelet-based compressive imaging; 17. Total variation minimization; Part V. From Compressed Sensing to Deep Learning: 18. Neural networks and deep learning; 19. Deep learning for compressive imaging; 20. Accuracy and stability of deep learning for compressive imaging; 21. Stable and accurate neural networks for compressive imaging; 22. Epilogue; Appendices: A. Linear Algebra; B. Functional analysis; C. Probability; D. Convex analysis and convex optimization; E. Fourier transforms and series; F. Properties of Walsh functions and the Walsh transform; Notation; Abbreviations; References; Index.

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Book SynopsisIn recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis. The development of a theoretical foundation to guarantee the success of these algorithms constitutes one of the most active and exciting research topics in applied mathematics. This book presents the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field. It serves both as a starting point for researchers and graduate students in computer science, mathematics, and statistics trying to get into the field and as an invaluable reference for future research.Table of Contents1. The modern mathematics of deep learning Julius Berner, Philipp Grohs, Gitta Kutyniok and Philipp Petersen; 2. Generalization in deep learning Kenji Kawaguchi, Leslie Pack Kaelbling, and Yoshua Bengio; 3. Expressivity of deep neural networks Ingo Gühring, Mones Raslan and Gitta Kutyniok; 4. Optimization landscape of neural networks René Vidal, Zhihui Zhu and Benjamin D. Haeffele; 5. Explaining the decisions of convolutional and recurrent neural networks Wojciech Samek, Leila Arras, Ahmed Osman, Grégoire Montavon and Klaus-Robert Müller; 6. Stochastic feedforward neural networks: universal approximation Thomas Merkh and Guido Montúfar; 7. Deep learning as sparsity enforcing algorithms A. Aberdam and J. Sulam; 8. The scattering transform Joan Bruna; 9. Deep generative models and inverse problems Alexandros G. Dimakis; 10. A dynamical systems and optimal control approach to deep learning Weinan E, Jiequn Han and Qianxiao Li; 11. Bridging many-body quantum physics and deep learning via tensor networks Yoav Levine, Or Sharir, Nadav Cohen and Amnon Shashua.

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Book SynopsisGet started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book.  With this book, you''ll be able to tackle some of today''s real world big data, smart bots, and other complex data problems. You''ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage.What You''ll Learn Use MATLAB for deep learning Discover neural networks and multi-layer neural networks Work with convolution and pooling layers Build a MNIST example with these layers WhoTable of Contents1. Machine Learning2. Neural Network3. Training of Multi-Layer Neural Network4. Neural Network and Classification5. Deep Learning6. Convolutional Neural Network

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Book SynopsisSome companies think that adopting devops means bringing in specialists or a host of new tools. With this practical guide, you'll learn why devops is a professional and cultural movement that calls for change from inside your organization.

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Book SynopsisToday, machine learning is being applied to a growing variety of problems in a bewildering variety of domains. A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to a concrete, real world problem. This book tackles this challenge through model-based machine learning which focuses on understanding the assumptions encoded in a machine learning system and their corresponding impact on the behaviour of the system.The key ideas of model-based machine learning are introduced through a series of case studies involving real-world applications. Case studies play a central role because it is only in the context of applications that it makes sense to discuss modelling assumptions. Each chapter introduces one case study and works through step-by-step to solve it using a model-based approach. The aim is not just to explain machine learning methods, but also showcase how to create, debug, and evolve them to solvTable of ContentsIntroduction. How Can Machine Learning Solve my Problem? 1. A Murder Mystery 2. Assessing People’s Skills Interlude. The Machine Learning Life Cycle 3. Meeting Your Match 4. Uncluttering Your Inbox 5. Making Recommendations 6. Understanding Asthma 7. Harnessing the Crowd 8. How to Read a Model Afterword

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Book SynopsisCSP notation has been used extensively for teaching and applying concurrency theory, ever since the publication of the text Communicating Sequential Processes by C.A.R. Hoare in 1985. Both a programming language and a specification language, the theory of CSP helps users to understand concurrent systems, and to decide whether a program meets its specification. As a member of the family of process algebras, the concepts of communication and interaction are presented in an algebraic style. An invaluable reference on the state of the art in CSP, Understanding Concurrent Systems also serves as a comprehensive introduction to the field, in addition to providing material for a number of more advanced courses. A first point of reference for anyone wanting to use CSP or learn about its theory, the book also introduces other views of concurrency, using CSP to model and explain these. The text is fully integrated with CSP-based tools such as FDR, and describes how to create new tools based on FDR. Most of the book relies on no theoretical background other than a basic knowledge of sets and sequences. Sophisticated mathematical arguments are avoided whenever possible. Topics and features: presents a comprehensive introduction to CSP; discusses the latest advances in CSP, covering topics of operational semantics, denotational models, finite observation models and infinite-behaviour models, and algebraic semantics; explores the practical application of CSP, including timed modelling, discrete modelling, parameterised verifications and the state explosion problem, and advanced topics in the use of FDR; examines the ability of CSP to describe and enable reasoning about parallel systems modelled in other paradigms; covers a broad variety of concurrent systems, including combinatorial, timed, priority-based, mobile, shared variable, statecharts, buffered and asynchronous systems; contains exercises and case studies to support the text; supplies further tools and information at the associated website: http://www.comlab.ox.ac.uk/ucs/. From undergraduate students of computer science in need of an introduction to the area, to researchers and practitioners desiring a more in-depth understanding of theory and practice of concurrent systems, this broad-ranging text/reference is essential reading for anyone interested in Hoare’s CSP.Trade ReviewFrom the reviews:“This book is divided into four parts … . Part I is designed for an audience of both undergraduate and graduate computer science students. … Part II is designed for people who are familiar with Part I and have fairly theoretical interests. … Part III is intended for people who … want to be able to use them in a better way, or who are specifically interested in timed systems. Part IV is designed for people who already understand CSP.” (Günther Bauer, Zentralblatt MATH, Vol. 1211, 2011)Table of ContentsPart I: A Foundation Course in CSP Building a Simple Sequential Process Understanding CSP Parallel Operators CSP Case Studies Hiding and Renaming Beyond Traces Further Operators Using FDR Part II: Theory Operational Semantics Denotational Semantics and Behavioural Models Finite Observation Models Infinite-behaviour Models The Algebra of CSP Part III: Using CSP Timed Systems 1: tock-CSP Timed Systems 2: Discrete Timed CSP More About FDR State Explosion and Parameterised Verification Part IV: Exploring Concurrency Shared-variable Programs Understanding Shared-variable Concurrency Priority and Mobility

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Book SynopsisThis book is Open Access under a CC BY licence. This book, LNCS 11429, is part III of the proceedings of the 25th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2019, which took place in Prague, Czech Republic, in April 2019, held as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2019. It's a special volume on the occasion of the 25 year anniversary of TACAS. Table of ContentsTOOLympics 2019: An Overview of Competitions in Formal Methods.- Confluence Competion 2019.- International Competition on Runtime Verification (CRV).- The Model Checking Contest (2019).- The 2019 Comparison of Tools for the Analysis of Quantitative Formal Models.- The Rewrite Engines Competitions: A RECtrospective.- RERS 2019: Combining Synthesis with Real-World Models.- SL-COMP: Competition of Solvers for Separation Logic.- Automatic Verification of C and Java Programs: SV-COMP 2019.- The Termination and Complexity Competition.- Competition on Software Testing (Test-Comp).- VerifyThis - Verification Competition with a Human Factor.- SV-COMP 2019.- CBMC Path: A Symbolic Execution Retrofit of the C Bounded Model Checker (Competition Contribution).- Extending DIVINE with Symbolic Verification using SMT (Competition Contribution).- ESBMC v6.0: Verifying C Programs using k-Induction and Invariant Inference (Competition Contribution).- JBMC: Bounded Model Checking for Java Bytecode (Competition Contribution).- JayHorn: A Java Model Checker (Competition Contribution).- Java Pathfinder at SV-COMP 2019.- Pinaka: Symbolic Execution meets Incremental Solving (Competition Contribution).- PeSCo: Predicting Sequential Combinations of Verifiers (Competition Contribution).- Symbolic Pathfinder for SV-COMP.- VeriFuzz: Program Aware Fuzzing.- VIAP 1.1 (Competition Contribution).

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Book SynopsisThis book constitutes the proceedings of the 18th International Conference on Unconventional Computation and Natural Computation, UCNC 2019, held in Tokyo, Japan, in June 2019.The 19 full papers presented were carefully reviewed and selected from 32 submissions. The papers cover topics such as hypercomputation; chaos and dynamical systems based computing; granular, fuzzy and rough computing; mechanical computing; cellular, evolutionary, molecular, neural, and quantum computing; membrane computing; amorphous computing, swarm intelligence; artificial immune systems; physics of computation; chemical computation; evolving hardware; the computational nature of self-assembly, developmental processes, bacterial communication, and brain processes.Table of ContentsInvited Paper.- Co-designing the computational model and the computing substrate.- Contributed Papers.- Generalized Membrane Systems with Dynamical Structure, Petri Nets, and Multiset Approximation Spaces.- Quantum Dual Adversary for Hidden Subgroups and Beyond.- Further Properties of Self-assembly by Hairpin Formation.- The Role of Structure and Complexity on Reservoir Computing Quality.- Lindenmayer Systems and Global Transformations.- Swarm-based multiset rewriting computing models.- DNA Origami Words and Rewriting Systems.- Computational Limitations of Affine Automata.- An Exponentially Growing Nubot System Without State Changes.- Impossibility of Sufficiently Simple Chemical Reaction Network Implementations in DNA Strand Displacement.- Quantum Algorithm for Dynamic Programming Approach for DAGs. Applications for Zhegalkin Polynomial Evaluation and Some Problems on DAGs.- Viewing rate-based neurons as biophysical conductance outputting models.- The Lyapunov Exponents of Reversible Cellular Automata Are Uncomputable.- Geometric Tiles and Powers and Limitations of Geometric Hindrance in Self-Assembly.- DNA Computing Units Based on Fractional Coding.- The role of the representational entity in physical computing.- OIM: Oscillator-based Ising Machines for Solving Combinatorial Optimisation Problems.- Relativizations of Nonuniform Quantum Finite Automata Families.- Self-stabilizing Gellular Automata.

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Book SynopsisThis English version of Ruslan L. Stratonovich’s Theory of Information (1975) builds on theory and provides methods, techniques, and concepts toward utilizing critical applications. Unifying theories of information, optimization, and statistical physics, the value of information theory has gained recognition in data science, machine learning, and artificial intelligence. With the emergence of a data-driven economy, progress in machine learning, artificial intelligence algorithms, and increased computational resources, the need for comprehending information is essential. This book is even more relevant today than when it was first published in 1975. It extends the classic work of R.L. Stratonovich, one of the original developers of the symmetrized version of stochastic calculus and filtering theory, to name just two topics.Each chapter begins with basic, fundamental ideas, supported by clear examples; the material then advances to great detail and depth. The reader is not required to be familiar with the more difficult and specific material. Rather, the treasure trove of examples of stochastic processes and problems makes this book accessible to a wide readership of researchers, postgraduates, and undergraduate students in mathematics, engineering, physics and computer science who are specializing in information theory, data analysis, or machine learning.Trade Review“The book could be useful in advanced graduate courses with students, who are not afraid of integrals and probabilities.” (Jaak Henno, zbMATH 1454.94002, 2021)Table of Contents

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Book SynopsisThis book constitutes the proceedings of the 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, held in Olslo, Norway, in September 2019. The 16 revised full papers,12 short papers and 18 poster papers presented were carefully reviewed and selected from 75 submissions. The general theme of TPDL 2019 was Connecting with Communities and so the papers attempt to facilitate establishing connections and convergences between diverse research communities such as Digital Humanities, Information Sciences and others that could benefit from ecosystems offered by digital libraries and repositories. To become especially useful to the diverse research and practitioner communities digital libraries need to consider special needs and requirements for effective data utilization, management and exploitation.Table of ContentsConer: A Collaborative Approach for Long-Tail Named Entity Recognition in Scientific Publications.- An unsupervised method for concept association analysis in text collections.- Linking Semantic Fingerprints of Literature.- Learning to Rank Claim-Evidence Pairs to Assist Scientific-Based Argumentation.- The OpenAIRE Research Community Dashboard: on Blending Scientific Workows and Scientific Publishing.- A Framework for Citing Nanopublications.- Analysis of Transaction Logs from National Museums Liverpool.- Knowledge Graph Implementation of Archival Descriptions through CIDOC-CRM.- Investigating Correlations of Inter-coder Agreement and Machine Annotation Performance for Historical Video Data.- Who is Mona L.? Identifying Mentions of Artworks in Historical Archives.- Gatekeeper: Quantifying the Impacts of Service to the Scientific Community.- A Study on the Readability of Scientific Publications.- Interdisciplinary Collaborations in the Brazilian Scientific Community.- Exploring Scholarly Data by Semantic Query on Knowledge Graph Embedding Space.- The Memento Tracer Framework: Balancing Quality and Scalability for Web Archiving.- The immigration dilemma; Legal, ethical and practical issues in creating a living, growing archive.- Segmenting User Sessions in Search Engine Query Logs Leveraging Word Embeddings.- A Human-friendly Query Generation Frontend for a Scientific Events Knowledge Graph.- User Interface for Interactive Scientific Publications: A Design Case Study.- Stable Word-clouds for Visualising Text-changes over Time.- A Hierarchical Label Network for Multi-Label EuroVoc Classification of Legislative Contents.- Can Language Inference Support Metadata Generation?.- Information Governance Maturity Assessment using Enterprise Architecture Model Analysis and Description Logics.- Finding Documents Related to Taiwan in the Veritable Records of Qing Using Relevance Feedback.- Fake News Detection with the New German Dataset "GermanFakeNC".- The CSO Classifier: Ontology-Driven Detection of Research Topics in Scholarly Articles.- Non-parametric Subject Prediction.- Visual Summarization of Scholarly Videos using Word Embeddings and Keyphrase Extraction.- Towards Serendipitous Research Paper Recommender using Tweets and Diversification.- Enriching the Cultural Heritage Metadata Using Historical Events: a Graph-Based Representation.- Open Research Knowledge Graph: A System Walkthrough.- The Biodiversity Heritage Library: Unveiling a World of Knowledge About Life on Earth.- Clipping the Page { Automatic Article Detection and Marking Software in Production of Newspaper Clippings in a Digitized Historical Journalistic Collection.- Document recommendations in Slovenian academic digital libraries.- An Evaluation of the Effect of Reference Strings and Segmentation on Citation Matching.- A la Carte: Turning Historical Menu into Menu Network.- Semantic Representation of Scientific Publications.- Determining How Citations Are Used in Citation Contexts.- Dendro: a FAIR, open-source data sharing platform.- User's Behavior in Digital Libraries: Process Mining Exploration.- SciTo Trends: Visualising Scientific Topic Trends.- The-Shelf Semantic Author Name Disambiguation for Bibliographic Data Bases.- Rending Behaviour in Educational Search.- Qatar Digital Library as a Platform for Digital Repatriation of Qatar's Cultural Heritage.- Correcting and redesigning metadata for the excavation of an archaeological site.- Topic Modelling vs Distant Supervision: A Comparative Evaluation based on the Classification of Parliamentary Enquiries.

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Book SynopsisThis graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number of exercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization. Table of ContentsIntroduction.- Matrix analysis and differentiation.- Matrix manifolds in MDA.- Principal component analysis (PCA).- Factor analysis (FA).- Procrustes analysis (PA).- Linear discriminant analysis (LDA).- Canonical correlation analysis (CCA).- Common principal components (CPC).- Metric multidimensional scaling (MDS) and related methods.- Data analysis on simplexes.

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Book SynopsisThis survey of computability theory offers the techniques and tools that computer scientists (as well as mathematicians and philosophers studying the mathematical foundations of computing) need to mathematically analyze computational processes and investigate the theoretical limitations of computing. Beginning with an introduction to the mathematisation of “mechanical process” using URM programs, this textbook explains basic theory such as primitive recursive functions and predicates and sequence-coding, partial recursive functions and predicates, and loop programs. Advanced chapters cover the Ackerman function, Tarski’s theorem on the non-representability of truth, Goedel’s incompleteness and Rosser’s incompleteness theorems, two short proofs of the incompleteness theorem that are based on Lob's deliverability conditions, Church’s thesis, the second recursion theorem and applications, a provably recursive universal function for the primitive recursive functions, Oracle computations and various classes of computable functionals, the Arithmetical hierarchy, Turing reducibility and Turing degrees and the priority method, a thorough exposition of various versions of the first recursive theorem, Blum’s complexity, Hierarchies of primitive recursive functions, and a machine-independent characterisation of Cobham's feasibly computable functions.Trade Review“This textbook is suited for self-study … . As a second reading however a reader interested in rigorous proofs and/or different approaches to known concepts will benefit from this wealth of material.” (Dieter Riebesehl, zbMATH 1507.03002, 2023)Table of ContentsMathematical Background; a Review.- A Theory of Computability.- Primitive Recursive Functions.- Loop Programs.-The Ackermann Function.- (Un)Computability via Church's Thesis.- Semi-Recursiveness.- Yet another number-theoretic characterisation of P.- Godel's Incompleteness Theorem via the Halting Problem.- The Recursion Theorem.- A Universal (non-PR) Function for PR.- Enumerations of Recursive and Semi-Recursive Sets.- Creative and Productive Sets Completeness.- Relativised Computability.- POSSIBILITY: Complexity of P Functions.- Complexity of PR Functions.- Turing Machines and NP-Completeness.

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Book SynopsisThis book constitutes the proceedings of the 19th Russian Conference on Artificial Intelligence, RCAI 2021, held in Moscow, Russia, in October 2021. The 19 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 80 submissions. The conference deals with a wide range of topics, categorized into the following topical headings: cognitive research; data mining, machine learning, classification; knowledge engineering; multi-agent systems and robotics; natural language processing; fuzzy models and soft computer; intelligent systems; and tools for designing intelligent systems. Table of ContentsCognitive Research.- Heterogeneous Formal Neurons and Modeling of Multi-Transmitter Neural Ensembles.- Methods for Recognition of Frustration-Derived Reactions in Social Media.- Identification of the Network State Based on the ART-2 Neural Network with a Hierarchical Memory Structure in Parallel Mode.- Data Mining, Machine Learning, Classification.- Ranking Weibull Survival Model: Boosting Concordance Index of Weibull Time-to-event Prediction Model with Ranking Losses.- Predicting Different Health and Lifestyle Behaviors of Social Media Users.- Methods for Finding Consequences with Specified Properties.- Data Mining Methods for Analysis and Forecast of Emerging Technology Trend: A Systematic Mapping Study from SCOPUS Papers.- Machine Learning for Assessment of Cardiometabolic Risk Factors Predictive Potential and Prediction of Obstructive Coronary Arteries Lesions.- Knowledge Engineering.- Application of FCA for Domain Model Theory Investigation.- The Metagraph Model for Complex Networks: Definition, Calculus and Granulation Issues.- Subjective Expert Evaluations in the Model-Theoretic Representation of Object Domain Knowledge.- Multiagent Systems and Robotics.- Q-Mixing Network for Multi-Agent Path Finding in Partially Observable Grid Environments.- Subdefinite Computations for Reducing the Search Space in Mobile Robot Localization Task.- Enhancing Exploration Algorithms for Navigation with Visual SLAM.- Natural Language Processing.- Relying on Discourse Trees to Extract Medical Ontologies from Text.- TITANIS: A Tool for Intelligent Text Analysis in Social Media.- Approach to the Automated Development of Scientific Subject Domain Ontologies Based on Heterogeneous Ontology Design Patterns.- Fuzzy Models and Soft Computing.- PC-algorithm of Algebraic Bayesian Network Secondary Structure Training.- Logistic-based Design of Fuzzy Interpretable Classifiers.- Intelligent Systems.- Knowledge-Based Diagnostic System with a Precedent Library.- Semiotic Models in Monitoring and Decision Support Systems.- Cognitive Patterns for Semantic Presentation of Natural-language Descriptions of Well-formalizable Problems.- Detecting Anomalous Behavior of Users of Data Centers based on the Application of Artificial Neural Networks.- Tools for Designing Intelligent Systems.- Study of the Feasibility of Creating of a Real-time Neuronetwork Infrared Ground Objects Recognition System.- The Implementation of the Ontological Approach to Control of the Processes of Designing Integrated Expert Systems Based on the Problem-oriented Methodology.- A Module for Industrial Safety Inspection Planning Based on Self-organization.-

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