Computer Technology and Computer Programming

Text-to-Speech Synthesis provides a complete, end-to-end account of the process of generating speech by computer. Giving an in-depth explanation of all aspects of current speech synthesis technology, it assumes no specialised prior knowledge. Introductory chapters on linguistics, phonetics, signal processing and speech signals lay the foundation, with subsequent material explaining how this knowledge is put to use in building practical systems that generate speech. Including coverage of the very latest techniques such as unit selection, hidden Markov model synthesis, and statistical text analysis, explanations of the more traditional techniques such as format synthesis and synthesis by rule are also provided. Weaving together the various strands of this multidisciplinary field, the book is designed for graduate students in electrical engineering, computer science, and linguistics. It is also an ideal reference for practitioners in the fields of human communication interaction and telep

Discrete optimization problems are everywhere, from traditional operations research planning (scheduling, facility location and network design); to computer science databases; to advertising issues in viral marketing. Yet most such problems are NP-hard; unless P = NP, there are no efficient algorithms to find optimal solutions. This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. The book is organized around central algorithmic techniques for designing approximation algorithms, including greedy and local search algorithms, dynamic programming, linear and semidefinite programming, and randomization. Each chapter in the first section is devoted to a single algorithmic technique applied to several different problems, with more sophisticated treatment in the second section. The book also covers methods for proving that optimization problems are hard to approximate. Designed as a textbook for graduate-level algorithm courses

This collection of articles by well-known experts was originally published in 2000 and is intended for researchers in computer science, practitioners of formal methods, and computer programmers working in safety-critical applications or in the technology of component-based systems. The work brings together several elements of this area that were fast becoming the focus of much research and practice in computing. The introduction by Clemens Szyperski gives a snapshot of research in the field. About half the articles deal with theoretical frameworks, models, and systems of notation; the rest of the book concentrates on case studies by researchers who have built prototype systems and present findings on architectures verification. The emphasis is on advances in the technological infrastructure of component-based systems; how to design and specify reusable components; and how to reason about, verify, and validate systems from components. Thus the book shows how theory might move into pract

This collection of articles by well-known experts was originally published in 2000 and is intended for researchers in computer science, practitioners of formal methods, and computer programmers working in safety-critical applications or in the technology of component-based systems. The work brings together several elements of this area that were fast becoming the focus of much research and practice in computing. The introduction by Clemens Szyperski gives a snapshot of research in the field. About half the articles deal with theoretical frameworks, models, and systems of notation; the rest of the book concentrates on case studies by researchers who have built prototype systems and present findings on architectures verification. The emphasis is on advances in the technological infrastructure of component-based systems; how to design and specify reusable components; and how to reason about, verify, and validate systems from components. Thus the book shows how theory might move into pract

The Second International Congress of Applied Linguistics, held in Cambridge (8–12 September 1969), provided papers from all over the world to different subjects within the linguistic family. These are: linguistics applied to literary texts, computer analysis of texts, psychology of first and second language learning, speech research, technology of language learning, language teaching and test material and methodology, lexicography, theory of translation, contrastive linguistics, and sociolinguistics. This book is a fascinating and useful work of reference for all concerned with applied linguistics.

Human factors is one of the critical issues in Information Technology, as industry realizes the need to change from technology-oriented goals to meet the demands of computer users. Human factors can help to improve Informatics Usability for real people, and to reduce the huge people-costs of human machine interactions. This book has been developed from lectures given at an Advanced Study course, sponsored by the European Science and Technology Research Committee of the Commission of the European Communities (CREST), and by the Science and Engineering Research Council (SERC) of the UK. It has three objectives: 1. To review the knowledge and methods available from the field of human factors for improving the usability of informatics systems; 2. To describe recent theoretical and methodological developments in the area; 3. To stimulate increased application of this expertise.

Human factors is one of the critical issues in Information Technology, as industry realizes the need to change from technology-oriented goals to meet the demands of computer users. Human factors can help to improve Informatics Usability for real people, and to reduce the huge people-costs of human machine interactions. This book has been developed from lectures given at an Advanced Study course, sponsored by the European Science and Technology Research Committee of the Commission of the European Communities (CREST), and by the Science and Engineering Research Council (SERC) of the UK. It has three objectives: 1. To review the knowledge and methods available from the field of human factors for improving the usability of informatics systems; 2. To describe recent theoretical and methodological developments in the area; 3. To stimulate increased application of this expertise.

This is an up-to-date and integrated introduction to model theory, designed to be used for graduate courses (for students who are familiar with first-order logic), and as a reference for more experienced logicians and mathematicians. Model theory is concerned with the notions of definition, interpretation and structure in a very general setting, and is applied to a wide variety of other areas such as set theory, geometry, algebra (in particular group theory), and computer science (e.g. logic programming and specification). Professor Hodges emphasises definability and methods of construction, and introduces the reader to advanced topics such as stability. He also provides the reader with much historical information and a full bibliography, enhancing the book's use as a reference.

This is an up-to-date and integrated introduction to model theory, designed to be used for graduate courses (for students who are familiar with first-order logic), and as a reference for more experienced logicians and mathematicians. Model theory is concerned with the notions of definition, interpretation and structure in a very general setting, and is applied to a wide variety of other areas such as set theory, geometry, algebra (in particular group theory), and computer science (e.g. logic programming and specification). Professor Hodges emphasises definability and methods of construction, and introduces the reader to advanced topics such as stability. He also provides the reader with much historical information and a full bibliography, enhancing the book's use as a reference.

This book gives applications of the theory of process algebra, or Algebra of Communicating Processes (ACP), that is the study of concurrent or communicating processes studied using an algebraic framework. The approach is axiomatic; the authors consider structures that are some set of mostly equational axioms, which are equipped with several operators. Thus the term 'algebra' is used in the model-theoretic sense. The axiomatic approach enables one to organize the field of process theories. The theory is applied systematically to a number of situations, including systolic algorithms, semantics of an object-oriented language, and protocols. It will be welcomed by computer scientists working in parallel programming.

This is a textbook on graph theory, especially suitable for computer scientists but also suitable for mathematicians with an interest in computational complexity. Although it introduces most of the classical concepts of pure and applied graph theory (spanning trees, connectivity, genus, colourability, flows in networks, matchings and traversals) and covers many of the major classical theorems, the emphasis is on algorithms and thier complexity: which graph problems have known efficient solutions and which are intractable. For the intractable problems a number of efficient approximation algorithms are included with known performance bounds. Informal use is made of a PASCAL-like programming language to describe the algorithms. A number of exercises and outlines of solutions are included to extend and motivate the material of the text.

Written in a tutorial style, this comprehensive guide follows a structured approach explaining cloud techniques, models and platforms. Popular cloud services such as Amazon, Google and Microsoft Azure are explained in the text. The security risks and challenges of cloud computing are discussed in detail with useful examples. Emerging trends including mobile cloud computing and internet of things are discussed in the book for the benefit of the readers. Numerous review questions, multiple choice exercises and case studies facilitate enhanced understanding. This textbook is ideal for undergraduate and graduate students of computer science engineering, and information technology.

An illustrated guide to exploring the Universe in three dimensions.Astronomers have made remarkable discoveries about our Universe, despite their reliance on the flat projection, or 2D view, the sky has offered them. But now, drawing on the vast stores of data available from telescopes and observatories on the ground and in space, astronomers are using 3D technology to go beyond a flattened view of the cosmos. In Stars in Your Hand, Kimberly Arcand and Megan Watzke offer an illustrated guide to exploring the Universe in three dimensions, with easy-to-follow instructions for creating models of stars and constellations using a 3D printer and 3D computer imaging. Stars in Your Hand and 3D technology make learning about space an adventure. Intrigued by the stunning images from high-powered telescopes? Using this book, you can fly virtually through a 3D spacescape and hold models of cosmic objects in your hand. Arcand and Watzke outline advances in 3D technology, describe some amazing recen

This book is an up-to-date introduction to the quantum theory of measurement, a fast developing field of intense current interest to scientists and engineers for its potential high technology applications. It is also a subject of importance to students for its central role in the foundations of quantum mechanics. Although the main principles of the field were elaborated in the 1930s by Bohr, Schrödinger, Heisenberg, von Neumann and Mandelstam, it was not until the 1980s that technology became sufficiently advanced to allow its application in real experiments. Quantum measurement is now central to many ultra-high technology developments, such as squeezed light, single atom traps, and searches for gravitational radiation. It is also considered to have great promise for computer science and engineering, particularly for its applications in information processing and transfer. The book contains a pedagogical introduction to the relevant theory written at a level accessible to those with on

This book is an up-to-date introduction to the quantum theory of measurement, a fast developing field of intense current interest to scientists and engineers for its potential high technology applications. It is also a subject of importance to students for its central role in the foundations of quantum mechanics. Although the main principles of the field were elaborated in the 1930s by Bohr, Schrödinger, Heisenberg, von Neumann and Mandelstam, it was not until the 1980s that technology became sufficiently advanced to allow its application in real experiments. Quantum measurement is now central to many ultra-high technology developments, such as squeezed light, single atom traps, and searches for gravitational radiation. It is also considered to have great promise for computer science and engineering, particularly for its applications in information processing and transfer. The book contains a pedagogical introduction to the relevant theory written at a level accessible to those with on

A systematic program design method can help developers ensure the correctness and performance of programs while minimizing the development cost. This book describes a method that starts with a clear specification of a computation and derives an efficient implementation by step-wise program analysis and transformations. The method applies to problems specified in imperative, database, functional, logic and object-oriented programming languages with different data, control and module abstractions. Designed for courses or self-study, this book includes numerous exercises and examples that require minimal computer science background, making it accessible to novices. Experienced practitioners and researchers will appreciate the detailed examples in a wide range of application areas including hardware design, image processing, access control, query optimization and program analysis. The last section of the book points out directions for future studies.

A systematic program design method can help developers ensure the correctness and performance of programs while minimizing the development cost. This book describes a method that starts with a clear specification of a computation and derives an efficient implementation by step-wise program analysis and transformations. The method applies to problems specified in imperative, database, functional, logic and object-oriented programming languages with different data, control and module abstractions. Designed for courses or self-study, this book includes numerous exercises and examples that require minimal computer science background, making it accessible to novices. Experienced practitioners and researchers will appreciate the detailed examples in a wide range of application areas including hardware design, image processing, access control, query optimization and program analysis. The last section of the book points out directions for future studies.

The study of computational processes based on the laws of quantum mechanics has led to the discovery of new algorithms, cryptographic techniques, and communication primitives. This book explores quantum computation from the perspective of the branch of theoretical computer science known as semantics, as an alternative to the more well-known studies of algorithmics, complexity theory, and information theory. It collects chapters from leading researchers in the field, discussing the theory of quantum programming languages, logics and tools for reasoning about quantum systems, and novel approaches to the foundations of quantum mechanics. This book is suitable for graduate students and researchers in quantum information and computation, as well as those in semantics, who want to learn about a new field arising from the application of semantic techniques to quantum information and computation.

This book was first published in 1970. It addresses the increasing use of digital computers for equilibrium calculations in high temperature, high pressure processes, in rocketry and in explosives technology. It surveys the numerical techniques developed over the fifteen to twenty years preceding its publication. The authors derive the equations describing equilibria in different types of system and outline the effect of variation of the parameters of the system on the equilibrium composition. They discuss critically the available methods of solution of the chemical equilibrium problem, both in the minimization and non-linear equations form, and indicate the factors that should be taken into account in selecting the optimum method of solution for a particular problem and computer. The fundamental chemical and thermodynamic analytic material was selected so as to make the book fully accessible for students of chemical engineering, explosives and technology.

Python is today's fastest growing programming language. This engaging and refreshingly different guide breaks down the skills into clear step-by-step chunks and explains the theory using brief easy-to-understand language. Rather than bamboozling readers with pages of mind-numbing technical jargon, this book includes 150 practical challenges, putting the power in the reader's hands. Through creating programs to solve these challenges the reader will quickly progress from mastering the basics to confidently using subroutines, a graphical user interface, and linking to external text, csv and SQL files. This book is perfect for anyone who wants to learn how to program with Python. In particular, students starting out in computer science and teachers who want to improve their confidence in Python will find here a set of ready-made challenges for classroom use.

Reactive flows encompass a broad range of physical phenomena, interacting over many different time and space scales. Such flows occur in combustion, chemical lasers, the earth's oceans and atmosphere, and stars and interstellar space. Despite the obvious physical differences in these flows, there is a striking similarity in the forms of their descriptive equations. Thus, the considerations and procedures for constructing numerical models of these systems are also similar, and these similarities can be exploited. Moreover, using the latest technology, what were once difficult and expensive computations can now be done on desktop computers. This book takes account of the explosive growth in computer technology and the greatly increased capacity for solving complex reactive flow problems that have occurred since the first edition of Numerical Simulation of Reactive Flow was published in 1987. It presents algorithms useful for reactive flow simulations, describes trade-offs involved in the

Reactive flows encompass a broad range of physical phenomena, interacting over many different time and space scales. Such flows occur in combustion, chemical lasers, the earth's oceans and atmosphere, and stars and interstellar space. Despite the obvious physical differences in these flows, there is a striking similarity in the forms of their descriptive equations. Thus, the considerations and procedures for constructing numerical models of these systems are also similar, and these similarities can be exploited. Moreover, using the latest technology, what were once difficult and expensive computations can now be done on desktop computers. This book takes account of the explosive growth in computer technology and the greatly increased capacity for solving complex reactive flow problems that have occurred since the first edition of Numerical Simulation of Reactive Flow was published in 1987. It presents algorithms useful for reactive flow simulations, describes trade-offs involved in the

The authoritative reference on NEURON, the simulation environment for modeling biological neurons and neural networks that enjoys wide use in the experimental and computational neuroscience communities. This book shows how to use NEURON to construct and apply empirically based models. Written primarily for neuroscience investigators, teachers, and students, it assumes no previous knowledge of computer programming or numerical methods. Readers with a background in the physical sciences or mathematics, who have some knowledge about brain cells and circuits and are interested in computational modeling, will also find it helpful. The NEURON Book covers material that ranges from the inner workings of this program, to practical considerations involved in specifying the anatomical and biophysical properties that are to be represented in models. It uses a problem-solving approach, with many working examples that readers can try for themselves.

The authoritative reference on NEURON, the simulation environment for modeling biological neurons and neural networks that enjoys wide use in the experimental and computational neuroscience communities. This book shows how to use NEURON to construct and apply empirically based models. Written primarily for neuroscience investigators, teachers, and students, it assumes no previous knowledge of computer programming or numerical methods. Readers with a background in the physical sciences or mathematics, who have some knowledge about brain cells and circuits and are interested in computational modeling, will also find it helpful. The NEURON Book covers material that ranges from the inner workings of this program, to practical considerations involved in specifying the anatomical and biophysical properties that are to be represented in models. It uses a problem-solving approach, with many working examples that readers can try for themselves.

Seismic Ray Theory presents a comprehensive treatment of the seismic ray method. This method plays an important role in seismology, seismic exploration, and in the interpretation of seismic measurements. Many concepts which extend the possibilities and increase the efficiency of the seismic ray method are included. The book has a tutorial character: derivations start with a relatively simple problem, in which the main ideas are easier to explain, and then advance to more complex problems. Most of the derived equations in the book are expressed in algorithmic form and may be used directly for computer programming. This book will prove to be an invaluable advanced textbook and reference volume in all academic institutions in which seismology is taught or researched. It will also be an invaluable resource in the research and exploration departments of the petroleum industry and in geological surveys.

Seismic Ray Theory presents a comprehensive treatment of the seismic ray method. This method plays an important role in seismology, seismic exploration, and in the interpretation of seismic measurements. Many concepts which extend the possibilities and increase the efficiency of the seismic ray method are included. The book has a tutorial character: derivations start with a relatively simple problem, in which the main ideas are easier to explain, and then advance to more complex problems. Most of the derived equations in the book are expressed in algorithmic form and may be used directly for computer programming. This book will prove to be an invaluable advanced textbook and reference volume in all academic institutions in which seismology is taught or researched. It will also be an invaluable resource in the research and exploration departments of the petroleum industry and in geological surveys.

This book answers one of the most critical questions of our time, does the vast connectivity afforded by mobile and social media lead to more personal connection with one another? It offers an evidence-based account of the role of technology in close relationships that confronts such pressing questions as where face-to-face communication belongs in this digital age, whether social media is harmful to our well-being, and how online communication spills-over into our offline communication and relationships. Each chapter explores the positive and negative influences of media on relationships, coalescing into a balanced assessment of how technological advancement has altered our connections with each other. By zeroing in on communication with the most important people in our lives and tracing the changes in computer-mediated communication over time, Relating Through Technology focuses the conversation about media on its use in our everyday lives and relationships.

Bringing together experts in multimodal signal processing, this book provides a detailed introduction to the area, with a focus on the analysis, recognition and interpretation of human communication. The technology described has powerful applications. For instance, automatic analysis of the outputs of cameras and microphones in a meeting can make sense of what is happening – who spoke, what they said, whether there was an active discussion and who was dominant in it. These analyses are layered to move from basic interpretations of the signals to richer semantic information. The book covers the necessary analyses in a tutorial manner, going from basic ideas to recent research results. It includes chapters on advanced speech processing and computer vision technologies, language understanding, interaction modeling and abstraction, as well as meeting support technology. This guide connects fundamental research with a wide range of prototype applications to support and analyze group interac

Explore the frontier of device engineering by applying optimization to nanoscience and device design. This cutting-edge work shows how robust, manufacturable designs that meet previously unobtainable system specifications can be created using a combination of modern computer power, adaptive algorithms, and realistic device-physics models. Applying this method to nanoscience is a path to creating new devices with new functionality, and it could be the key design element in making nanoscience a practical technology. Basic introductory examples along with MATLAB code are included, through to more formal and sophisticated approaches, and specific applications and designs are examined. Essential reading for researchers and engineers in electronic devices, nanoscience, materials science, applied mathematics, and applied physics.

Optical techniques have a huge range of potential applications in signal processing and in the interconnection of digital computing systems. This 1995 book provides a detailed review of the key issues which must be addressed in the design, evaluation and implementation of practical systems for signal processing and optical interconnection. Considerations such as the computer modelling of optical design limitations, the size and noise characteristics of optical modulators, and the relative merits of free-space and guided-wave optical technology in different processing systems, are all discussed in detail. The book will be of great interest to optical researchers and designers, and to anyone wishing to learn about the basic techniques of optical processing.

Optical techniques have a huge range of potential applications in signal processing and in the interconnection of digital computing systems. This 1995 book provides a detailed review of the key issues which must be addressed in the design, evaluation and implementation of practical systems for signal processing and optical interconnection. Considerations such as the computer modelling of optical design limitations, the size and noise characteristics of optical modulators, and the relative merits of free-space and guided-wave optical technology in different processing systems, are all discussed in detail. The book will be of great interest to optical researchers and designers, and to anyone wishing to learn about the basic techniques of optical processing.

Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. Accompanying the mathematical derivations are full implementations of dozens of numerical methods in Python, as well as more than 250 end-of-chapter problems. Numerical methods and physics examples are clearly separated, allowing this introductory book to be later used as a reference; the penultimate section in each chapter is an in depth project, tackling physics problems which cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the

Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. Accompanying the mathematical derivations are full implementations of dozens of numerical methods in Python, as well as more than 250 end-of-chapter problems. Numerical methods and physics examples are clearly separated, allowing this introductory book to be later used as a reference; the penultimate section in each chapter is an in depth project, tackling physics problems which cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the

Fortran is a computer language that has been around for a quarter of a century, and is still much used despite predictions throughout its life that it would be replaced by more elegant languages. But Fortran is still the only language in which it is possible to write truly portable programs. Using his own special formula, Donald Alcock now does for Fortran what he did for BASIC in his earlier book, Illustrating BASIC. The Fortran described and illustrated is that defined by the American National Standards Institute in 1966 but with allusions to the same Institute's standard published in 1978. For both the person who is new to computers and programming, and the person who has met only BASIC before, this book will give an excellent introduction to standard Fortran; it also provides a reference manual for the language.

The core of scientific computing is designing, writing, testing, debugging and modifying numerical software for application to a vast range of areas: from graphics, meteorology and chemistry to engineering, biology and finance. Scientists, engineers and computer scientists need to write good code, for speed, clarity, flexibility and ease of re-use. Oliveira and Stewart's style guide for numerical software points out good practices to follow, and pitfalls to avoid. By following their advice, readers will learn how to write efficient software, and how to test it for bugs, accuracy and performance. Techniques are explained with a variety of programming languages, and illustrated with two extensive design examples, one in Fortran 90 and one in C++: other examples in C, C++, Fortran 90 and Java are scattered throughout the book. This manual of scientific computing style will be an essential addition to the bookshelf and lab of everyone who writes numerical software.

This book/CD bundle of the greatly expanded third edition of Numerical Recipes now has wider coverage than ever before, many new, expanded and updated sections, and two completely new chapters. Co-authored by four leading scientists from academia and industry, Numerical Recipes starts with basic mathematics and computer science and proceeds to complete, working routines. The informal, easy-to-read style that made earlier editions so popular is kept throughout. Highlights of the new material include: a new chapter on classification and inference, Gaussian mixture models, HMMs, hierarchical clustering, and SVMs; a new chapter on computational geometry, covering KD trees, quad- and octrees, Delaunay triangulation, and algorithms for lines, polygons, triangles, and spheres; interior point methods for linear programming; MCMC; an expanded treatment of ODEs with completely new routines; and many new statistical distributions. For support or further licence information please visit www.nr.com

Mathematics is not, and never will be, an empirical science, but mathematicians are finding that the use of computers and specialized software allows the generation of mathematical insight in the form of conjectures and examples, which pave the way for theorems and their proofs. In this way, the experimental approach to pure mathematics is revolutionizing the way research mathematicians work. As the first of its kind, this book provides material for a one-semester course in experimental mathematics that will give students the tools and training needed to systematically investigate and develop mathematical theory using computer programs written in Maple. Accessible to readers without prior programming experience, and using examples of concrete mathematical problems to illustrate a wide range of techniques, the book gives a thorough introduction to the field of experimental mathematics, which will prepare students for the challenge posed by open mathematical problems.

What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual pro

What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual pro

There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.