Probabilistic Graphical Model for Computer Vision

This book introduces an innovative collection of easy-to-use computer programs that have been developed to measure and model vocabulary knowledge. The book aims to help researchers discover new instru

This book examines the application of drawing in the design process of classical architecture, exploring how the tools and techniques of drawing developed for architecture subsequently shaped theories of vision and representations of the universe in science and philosophy. Building on recent scholarship that examines and reconstructs the design process of classical architecture, John R. Senseney focuses on technical drawing in the building trade as a model for the expression of visual order, showing that the techniques of ancient Greek drawing actively determined concepts about the world. He argues that the uniquely Greek innovations of graphic construction determined principles that shaped the massing, special qualities and refinements of buildings and the manner in which order itself was envisioned.

This practical and authoritative text/reference presents a broad introduction to the optimization methods used specifically in computer vision. In order to facilitate understanding, the presentation o

Graph Embedding for Pattern Recognition covers theory methods, computation, and applications widely used in statistics, machine learning, image processing, and computer vision. This book presents the

The potential of consumer depth cameras extends well beyond entertainment and gaming, to real-world commercial applications. This authoritative text reviews the scope and impact of this rapidly growin

A provocative blend of personal memoir, new science, and philosophical treatise, this book presents a fresh model for healing by rethinking our relationships with one another, the natural world, our b

This book examines the application of drawing in the design process of classical architecture, exploring how the tools and techniques of drawing developed for architecture subsequently shaped theories of vision and representations of the universe in science and philosophy. Building on recent scholarship that examines and reconstructs the design process of classical architecture, John R. Senseney focuses on technical drawing in the building trade as a model for the expression of visual order, showing that the techniques of ancient Greek drawing actively determined concepts about the world. He argues that the uniquely Greek innovations of graphic construction determined principles that shaped the massing, special qualities and refinements of buildings and the manner in which order itself was envisioned.

This volume contains a total of thirteen papers covering a variety of AI topics ranging from computer vision and robotics to intelligent modeling, neural networks and fuzzy logic. There are two gen

Computing developed as a branch of mathematics, only to drift away from this home as computer science diverged towards more general topics such as the theory of how a computer works. Recently the emphasis has become more mathematical and the new disciplines of software engineering and information technology have emerged. This book is designed to form the basis of a one year course in discrete mathematics for first year computer scientists or software engineers. The material presented covers much of undergraduate algebra with a particular bias towards the computing applications. Topics covered include mathematical logic, set theory, finite and infinite relations and mappings, graphs, graphical algorithms and axiom systems. It concludes with implementations of many of the algorithms in Modula-2 to illustrate how the mathematics may be turned into concrete calculations. Numerous examples and exercises are included with selected solutions to the problems appearing in the appendix. Discrete

Ever noticed how leadership theories can disintegrate in the face of real-world challenges? That’s frustrating, whether you’re a busy executive or a developing leader. On the other hand, purely reactive problem-solving is like bailing water from a ship without ever patching the leaks. With no reflection, no structure, no guiding vision, your temporary fixes won’t last, and soon you’re bailing water again.Author Jamie Ramsden has thrived in the leadership world as a successful executive, an elite coach, and an academic. Let’s Go! lays out his own powerful leadership framework, which merges hands-on business knowledge with profound insights into human motivations. The effective leader is a role model, a community builder, a sense maker, and a future shaper.In this inspirational book, Jamie blends theory and practical application to show you how to excel in each of these four leadership roles—and bring your team, your family, and your whole community along for the ride. Let’s Go! empowers

THE INSTANT NEW YORK TIMES BESTSELLER'A compelling vision of where the internet should go and how to get there.' Sam Altman, CEO, OpenAI_A potent exploration of the power of blockchains to reshape the future of the internet - and how that affects us all - from technology entrepreneur and startup investor Chris Dixon.The internet of today is a far cry from its early promise of a decentralized, democratic network of innovation, connection and freedom. In the past decade, it has fallen almost entirely under the control of a very small group of companies like Apple, Google, and Facebook.In Read Write Own, tech visionary Chris Dixon argues that the dream of a creative, entrepreneurial internet doesn't have to die and can, in fact, be saved with blockchain networks. He separates this movement, which aims to provide a solid foundation for everything from social networks to artificial intelligence to virtual worlds, from cryptocurrency speculation - a distinction he calls 'the computer vs the

THE INSTANT NEW YORK TIMES BESTSELLER‘A compelling vision of where the internet should go and how to get there.’ Sam Altman, CEO, OpenAI_A potent exploration of the power of blockchains to reshape the future of the internet – and how that affects us all – from technology entrepreneur and startup investor Chris Dixon. The internet of today is a far cry from its early promise of a decentralized, democratic network of innovation, connection and freedom. In the past decade, it has fallen almost entirely under the control of a very small group of companies like Apple, Google, and Facebook.In Read Write Own, tech visionary Chris Dixon argues that the dream of a creative, entrepreneurial internet doesn’t have to die and can, in fact, be saved with blockchain networks. He separates this movement, which aims to provide a solid foundation for everything from social networks to artificial intelligence to virtual worlds, from cryptocurrency speculation – a distinction he calls ‘the computer vs the

This new book on mathematical logic by Jeremy Avigad gives a thorough introduction to the fundamental results and methods of the subject from the syntactic point of view, emphasizing logic as the study of formal languages and systems and their proper use. Topics include proof theory, model theory, the theory of computability, and axiomatic foundations, with special emphasis given to aspects of mathematical logic that are fundamental to computer science, including deductive systems, constructive logic, the simply typed lambda calculus, and type-theoretic foundations. Clear and engaging, with plentiful examples and exercises, it is an excellent introduction to the subject for graduate students and advanced undergraduates who are interested in logic in mathematics, computer science, and philosophy, and an invaluable reference for any practicing logician's bookshelf.

Intended for researchers and practitioners in interaction design, this book shows how Bayesian models can be brought to bear on problems of interface design and user modelling. It introduces and motivates Bayesian modelling and illustrates how powerful these ideas can be in thinking about human-computer interaction, especially in representing and manipulating uncertainty. Bayesian methods are increasingly practical as computational tools to implement them become more widely available, and offer a principled foundation to reason about interaction design. The book opens with a self-contained tutorial on Bayesian concepts and their practical implementation, tailored for the background and needs of interaction designers. The contributed chapters cover the use of Bayesian probabilistic modelling in a diverse set of applications, including improving pointing-based interfaces; efficient text entry using modern language models; advanced interface design using cutting-edge techniques in Bayesia

The thirteenth-century allegorical dream vision, the Roman de la Rose, transformed how medieval literary texts engaged with philosophical ideas. Written in Old French, its influence dominated French, English and Italian literature for the next two centuries, serving in particular as a model for Chaucer and Dante. Jean de Meun's section of this extensive, complex and dazzling work is notable for its sophisticated responses to a whole host of contemporary philosophical debates. This collection brings together literary scholars and historians of philosophy to produce the most thorough, interdisciplinary study to date of how the Rose uses poetry to articulate philosophical problems and positions. This wide-ranging collection demonstrates the importance of the poem for medieval intellectual history and offers new insights into the philosophical potential both of the Rose specifically and of medieval poetry as a whole.

A Vintage Crime/Black Lizard Special Edition of The Postman Always Rings Twice by James M. Cain. Featuring an introduction by James Ellroy.When Frank, an amoral young drifter, gets thrown off a hay truck in the California desert, he ends up at a diner run by Cora and her inconvenient husband, Nick. This chance meeting puts them all on a sure path to perdition. First published in 1934 and banned in Boston for its explosive mixture of violence and eroticism, The Postman Always Rings Twice is a classic of the roman noir. It established James M. Cain as a major novelist with an unsparing vision of America's bleak underside and was acknowledged by Albert Camus as the model for The Stranger.

A bestselling author, neuroscientist, and computer engineer unveils a theory of intelligence that will revolutionize our understanding of the brain and the future of AI. For all of neuroscience's advances, we've made little progress on its biggest question: How do simple cells in the brain create intelligence? Jeff Hawkins and his team discovered that the brain uses maplike structures to build a model of the world-not just one model, but hundreds of thousands of models of everything we know. This discovery allows Hawkins to answer important questions about how we perceive the world, why we have a sense of self, and the origin of high-level thought. A Thousand Brains heralds a revolution in the understanding of intelligence. It is a big-think book, in every sense of the word.

This textbook for students in the health and social sciences covers the basics of linear model methods with a minimum of mathematics, assuming only a pre-calculus background. Numerous examples drawn from the news and current events with an emphasis on health issues, illustrate the concepts in an immediately accessible way. Methods covered include linear regression models, Poisson regression, logistic regression, proportional hazards regression, survival analysis, and nonparametric regression. The author emphasizes interpretation of computer output in terms of the motivating example. All of the R code is provided and carefully explained, allowing readers to quickly apply the methods to their own data. Plenty of exercises help students think about the issues involved in the analysis and its interpretation. Code and datasets are available for download from the book's website at www.cambridge.org/zelterman

Our world and the people within it are increasingly interpreted and classified by automated systems. At the same time, automated classifications influence what happens in the physical world. These entanglements change what it means to interact with governance, and shift what elements of our identity are knowable and meaningful. In this cyber-physical world, or 'world state', what is the role for law? Specifically, how should law address the claim that computational systems know us better than we know ourselves? Monitoring Laws traces the history of government profiling from the invention of photography through to emerging applications of computer vision for personality and behavioral analysis. It asks what dimensions of profiling have provoked legal intervention in the past, and what is different about contemporary profiling that requires updating our legal tools. This work should be read by anyone interested in how computation is changing society and governance, and what it is about p

Connecting theory with practice, this systematic and rigorous introduction covers the fundamental principles, algorithms and applications of key mathematical models for high-dimensional data analysis. Comprehensive in its approach, it provides unified coverage of many different low-dimensional models and analytical techniques, including sparse and low-rank models, and both convex and non-convex formulations. Readers will learn how to develop efficient and scalable algorithms for solving real-world problems, supported by numerous examples and exercises throughout, and how to use the computational tools learnt in several application contexts. Applications presented include scientific imaging, communication, face recognition, 3D vision, and deep networks for classification. With code available online, this is an ideal textbook for senior and graduate students in computer science, data science, and electrical engineering, as well as for those taking courses on sparsity, low-dimensional str

Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book’s website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook.The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about

Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and purposes of reading. Part 1 introduces basic concepts of graphs and deep learning; Part 2 discusses the most established methods from the basic to advanced settings; Part 3 presents the most typical applications including natural language processing, computer vision, data mining, biochemistry and healthcare; and Part 4 describes advances of methods and applications that tend to be important and promising for future research. The book is self-contained, making it accessible to a broader range of readers including (1) senior undergraduate and graduate students; (2) practitioners and project managers who want to adopt graph neural networks into their products and platforms; and (3) researchers without a computer science background who want to use graph neural networks to advance their disciplines.

This volume offers a carefully argued, compelling theory of bioethics while eliciting practical implications for a wide array of issues including medical assistance-in-dying, the right to health care, abortion, animal research, and the definition of death. The authors' dual-value theory features mid-level principles, a distinctive model of moral status, a subjective account of well-being, and a cosmopolitan view of global justice. In addition to ethical theory, the book investigates the nature of harm and autonomous action, personal identity theory, and the 'non-identity problem' associated with many procreative decisions. Readers new to particular topics will benefit from helpful introductions, specialists will appreciate in-depth theoretical explorations and a novel take on various practical issues, and all readers will benefit from the book's original synoptic vision of bioethics. This title is also available as Open Access on Cambridge Core.

This volume offers a carefully argued, compelling theory of bioethics while eliciting practical implications for a wide array of issues including medical assistance-in-dying, the right to health care, abortion, animal research, and the definition of death. The authors' dual-value theory features mid-level principles, a distinctive model of moral status, a subjective account of well-being, and a cosmopolitan view of global justice. In addition to ethical theory, the book investigates the nature of harm and autonomous action, personal identity theory, and the 'non-identity problem' associated with many procreative decisions. Readers new to particular topics will benefit from helpful introductions, specialists will appreciate in-depth theoretical explorations and a novel take on various practical issues, and all readers will benefit from the book's original synoptic vision of bioethics. This title is also available as Open Access on Cambridge Core.

WHEN I'M A SURGEON instils a belief in children that they can achieve greatness, fulfilling their dreams and potential. "Once children have a vision and believe in their goals - anything is possible." - Dr. Samantha Pillay.Girl Power! "You can't be what you can't see." -- Marian Wright Edelman; Famous Female Leader.Children assign gender stereotypes to jobs in early childhood. These gender stereotypes are influenced by who they know, what they see on TV and media, and they define their career aspirations. Dreams and aspirations lead to motivation, self-confidence, self-esteem and skills. Dr Samantha Pillay, surgeon and role-model, is no stranger to overcoming adversity. She finished school at age sixteen, after starting school in a wheelchair. She believes "Once children have a vision and believe in their goals - anything is possible."When I'm a Surgeon is a must-read for the next generation of leaders. Grab yours and inspire your favorite little ones. Consider purchasing an extra one

Discover the fundamental principles of biomedical measurement design and performance evaluation with this hands-on guide. Whether you develop measurement instruments or use them in novel ways, this practical text will prepare you to be an effective generator and consumer of biomedical data. Designed for both classroom instruction and self-study, it explains how information is encoded into recorded data and can be extracted and displayed in an accessible manner. Describes and integrates experimental design, performance assessment, classification, and system modelling. Combines mathematical concepts with computational models, providing the tools needed to answer advanced biomedical questions. Includes MATLAB® scripts throughout to help readers model all types of biomedical systems, and contains numerous homework problems, with a solutions manual available online. This is an essential text for advanced undergraduate and graduate students in bioengineering, electrical and computer engineer

Constraint Satisfaction Problems (CSPs) are natural computational problems that appear in many areas of theoretical computer science. Exploring which CSPs are solvable in polynomial time and which are NP-hard reveals a surprising link with central questions in universal algebra. This monograph presents a self-contained introduction to the universal-algebraic approach to complexity classification, treating both finite and infinite-domain CSPs. It includes the required background from logic and combinatorics, particularly model theory and Ramsey theory, and explains the recently discovered link between Ramsey theory and topological dynamics and its implications for CSPs. The book will be of interest to graduate students and researchers in theoretical computer science and to mathematicians in logic, combinatorics, and dynamics who wish to learn about the applications of their work in complexity theory.

The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field. It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting.This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice.

This textbook bypasses the need for advanced mathematics by providing in-text computer code, allowing students to explore Bayesian data analysis without the calculus background normally considered a prerequisite for this material. Now, students can use the best methods without needing advanced mathematical techniques. This approach goes beyond “frequentist” concepts of p-values and null hypothesis testing, using the full power of modern probability theory to solve real-world problems. The book offers a fully self-contained course, which demonstrates analysis techniques throughout with worked examples crafted specifically for students in the behavioral and neural sciences. The book presents two general algorithms that help students solve the measurement and model selection (also called “hypothesis testing”) problems most frequently encountered in real-world applications.

This textbook bypasses the need for advanced mathematics by providing in-text computer code, allowing students to explore Bayesian data analysis without the calculus background normally considered a prerequisite for this material. Now, students can use the best methods without needing advanced mathematical techniques. This approach goes beyond “frequentist” concepts of p-values and null hypothesis testing, using the full power of modern probability theory to solve real-world problems. The book offers a fully self-contained course, which demonstrates analysis techniques throughout with worked examples crafted specifically for students in the behavioral and neural sciences. The book presents two general algorithms that help students solve the measurement and model selection (also called “hypothesis testing”) problems most frequently encountered in real-world applications.

Web Semantics strengthen the description of web resources to exploit them better and make them more meaningful for both humans and machines, thereby contributing to the development of a knowledgeintensive data web. The world is experiencing the movement of concept from data to knowledge and the movement of web from document model to data model. The underlying idea is making the data machine understandable and processable.In the light of these trends, conciliation of Semantic and the Web is of paramount importance for further progress in the area. Web Semantics: Cutting Edge and Future Directions in Healthcare describes the three major components of the study of Semantic Web, namely Representation, Reasoning, and Security with a special focus on the healthcare domain. This book summarizes the trends and current research advances in web semantics, emphasizing the existing tools and techniques, methodologies, and research solutions.It provides easily comprehensible information on Web Sema

This research textbook, designed for young Human-Computer Interaction (HCI) researchers beginning their careers, surveys the research models and methods in use today and offers a general framework to bring together the disparate concepts. HCI spans many disciplines and professions, including information science, applied psychology, computer science, informatics, software engineering and social science making it difficult for newcomers to get a good overview of the field and the available approaches. The book's rigorous 'approach-and-framework' response is to the challenge of retaining growth and diversification in HCI research by building up a general framework from approaches for Innovation, Art, Craft, Applied, Science and Engineering. This general framework is compared with other HCI frameworks and theories for completeness and coherence, all within a historical perspective of dissemination success. Readers can use this as a model to design and assess their own research frameworks a

Most textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression. It is about using regression to solve real problems of comparison, estimation, prediction, and causal inference. Unlike other books, it focuses on practical issues such as sample size and missing data and a wide range of goals and techniques. It jumps right in to methods and computer code you can use immediately. Real examples, real stories from the authors' experience demonstrate what regression can do and its limitations, with practical advice for understanding assumptions and implementing methods for experiments and observational studies. They make a smooth transition to logistic regression and GLM. The emphasis is on computation in R and Stan rather than derivations, with code available online. Graphics and presentation aid understanding of the models and model fitting.

Most textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression. It is about using regression to solve real problems of comparison, estimation, prediction, and causal inference. Unlike other books, it focuses on practical issues such as sample size and missing data and a wide range of goals and techniques. It jumps right in to methods and computer code you can use immediately. Real examples, real stories from the authors' experience demonstrate what regression can do and its limitations, with practical advice for understanding assumptions and implementing methods for experiments and observational studies. They make a smooth transition to logistic regression and GLM. The emphasis is on computation in R and Stan rather than derivations, with code available online. Graphics and presentation aid understanding of the models and model fitting.

Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This introduction for researchers and graduate students is the first in-depth, comprehensive treatment of statistical and machine learning methods for neuroscience. The methods are demonstrated through case studies of real problems to empower readers to build their own solutions. The book covers a wide variety of methods, including supervised classification with non-probabilistic models (nearest-neighbors, classification trees, rule induction, artificial neural networks and support vector machines) and probabilistic models (discriminant analysis, logistic regression and Bayesian network classifiers), meta-classifiers, multi-dimensional classifiers and feature subset selection methods. Other parts of the book are devoted to association discovery with probabilistic graphical models (Bayesian networks and Markov networks) and spatial statistics with po

This book introduces Raspberry Pi, using real world applications in computer vision, machine learning, and deep learning. It provides a detailed, step-by-step, approach to application development for

Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction to the multi-armed bandit problem examines all the major settings, including stochastic, adversarial, and Bayesian frameworks. A focus on both mathematical intuition and carefully worked proofs makes this an excellent reference for established researchers and a helpful resource for graduate students in computer science, engineering, statistics, applied mathematics and economics. Linear bandits receive special attention as one of the most useful models in applications, while other chapters are dedicated to combinatorial bandits, ranking, non-stationary problems, Thompson sampling and pure exploration. The book ends with a peek into the world beyond bandits with an introduction to partial monitoring and learning in Markov decision processes.

Transfer learning deals with how systems can quickly adapt themselves to new situations, tasks and environments. It gives machine learning systems the ability to leverage auxiliary data and models to help solve target problems when there is only a small amount of data available. This makes such systems more reliable and robust, keeping the machine learning model faced with unforeseeable changes from deviating too much from expected performance. At an enterprise level, transfer learning allows knowledge to be reused so experience gained once can be repeatedly applied to the real world. For example, a pre-trained model that takes account of user privacy can be downloaded and adapted at the edge of a computer network. This self-contained, comprehensive reference text describes the standard algorithms and demonstrates how these are used in different transfer learning paradigms. It offers a solid grounding for newcomers as well as new insights for seasoned researchers and developers.

The thirteenth-century allegorical dream vision, the Roman de la Rose, transformed how medieval literary texts engaged with philosophical ideas. Written in Old French, its influence dominated French, English and Italian literature for the next two centuries, serving in particular as a model for Chaucer and Dante. Jean de Meun's section of this extensive, complex and dazzling work is notable for its sophisticated responses to a whole host of contemporary philosophical debates. This collection brings together literary scholars and historians of philosophy to produce the most thorough, interdisciplinary study to date of how the Rose uses poetry to articulate philosophical problems and positions. This wide-ranging collection demonstrates the importance of the poem for medieval intellectual history and offers new insights into the philosophical potential both of the Rose specifically and of medieval poetry as a whole.