This book is meant to provide an introduction to vectors, matrices, and least squares methods, basic topics in applied linear algebra. Our goal is to give the beginning student, with little or no prior exposure to linear algebra, a good grounding in the basic ideas, as well as an appreciation for how they are used in many applications, including data fitting, machine learning and artificial intelligence, to-mography, navigation, image processing, finance, and automatic control systems.
The background required of the reader is familiarity with basic mathematical notation. We use calculus in just a few places, but it does not play a critical role and is not a strict prerequisite. Even though the book covers many topics that are traditionally taught as part of probability and statistics, such as fitting mathematical models to data, no knowledge of or background in probability and statistics is needed.
The book covers less mathematics than a typical text on applied linear algebra. We use only one theoretical concept from linear algebra, linear independence, and only one computational tool, the QR factorization; our approach to most applications relies on only one method, least squares (or some extension). In this sense we aim for intellectual economy: With just a few basic mathematical ideas, con-cepts, and methods, we cover many applications. The mathematics we do present, however, is complete, in that we carefully justify every mathematical statement. In contrast to most introductory linear algebra texts, however, we describe many applications, including some that are typically considered advanced topics, like document classification, control, state estimation, and portfolio optimization.
The book does not require any knowledge of computer programming, and can be used as a conventional textbook, by reading the chapters and working the exercises that do not involve numerical computation. This approach however misses out on one of the most compelling reasons to learn the material: You can use the ideas and methods described in this book to do practical things like build a prediction model from data, enhance images, or optimize an investment portfolio. The growing power of computers, together with the development of high level computer languages and packages that support vector and matrix computation, have made it easy to use the methods described in this book for real applications. For this reason we hope that every student of this book will complement their study with computer programming exercises and projects, including some that involve real data. This book includes some generic exercises that require computation; additional ones, and the associated data files and language-specific resources, are available online.
If you read the whole book, work some of the exercises, and carry out computer exercises to implement or use the ideas and methods, you will learn a lot. While there will still be much for you to learn, you will have seen many of the basic ideas behind modern data science and other application areas. We hope you will be empowered to use the methods for your own applications.
The book is divided into three parts. Part I introduces the reader to vectors, and various vector operations and functions like addition, inner product, distance, and angle. We also describe how vectors are used in applications to represent word counts in a document, time series, attributes of a patient, sales of a product, an audio track, an image, or a portfolio of investments. Part II does the same for matrices, culminating with matrix inverses and methods for solving linear equa-tions. Part III, on least squares, is the payoff, at least in terms of the applications. We show how the simple and natural idea of approximately solving a set of over-determined equations, and a few extensions of this basic idea, can be used to solve many practical problems.
The whole book can be covered in a 15 week (semester) course; a 10 week (quarter) course can cover most of the material, by skipping a few applications and perhaps the last two chapters on nonlinear least squares. The book can also be used for self-study, complemented with material available online. By design, the pace of the book accelerates a bit, with many details and simple examples in parts I and II, and more advanced examples and applications in part III. A course for students with little or no background in linear algebra can focus on parts I and II, and cover just a few of the more advanced applications in part III. A more advanced course on applied linear algebra can quickly cover parts I and II as review, and then focus on the applications in part III, as well as additional topics.
We are grateful to many of our colleagues, teaching assistants, and students for helpful suggestions and discussions during the development of this book and the associated courses. We especially thank our colleagues Trevor Hastie, Rob Tibshirani, and Sanjay Lall, as well as Nick Boyd, for discussions about data fitting and classification, and Jenny Hong, Ahmed Bou-Rabee, Keegan Go, David Zeng, and Jaehyun Park, Stanford undergraduates who helped create and teach the course EE103. We thank David Tse, Alex Lemon, Neal Parikh, and Julie Lancashire for carefully reading drafts of this book and making many good suggestions.

Friedrich Nietzsche is one of the most influential thinkers of the past 150 years and On the Genealogy of Morality (1887) is his most important work on ethics and politics. A polemical contribution to moral and political theory, it offers a critique of moral values and traces the historical evolution of concepts such as guilt, conscience, responsibility, law and justice. This is a revised and updated 2006 edition of one of the most successful volumes to appear in Cambridge Texts in the History of Political Thought. Keith Ansell-Pearson modified his introduction to Nietzsche's classic text, and Carol Diethe incorporated a number of changes to the translation itself, reflecting the considerable advances in our understanding of Nietzsche. In this guise the Cambridge Texts edition of Nietzsche's Genealogy should continue to enjoy widespread adoption, at both undergraduate and graduate level.

In this book Rorty argues that thinkers such as Nietzsche, Freud, and Wittgenstein have enabled societies to see themselves as historical contingencies, rather than as expressions of underlying, ahistorical human nature or as realizations of suprahistorical goals. This ironic perspective on the human condition is valuable on a private level, although it cannot advance the social or political goals of liberalism. In fact Rorty believes that it is literature not philosophy that can do this, by promoting a genuine sense of human solidarity. A truly liberal culture, acutely aware of its own historical contingency, would fuse the private, individual freedom of the ironic, philosophical perspective with the public project of human solidarity as it is engendered through the insights and sensibilities of great writers. The book has a characteristically wide range of reference from philosophy through social theory to literary criticism. It confirms Rorty's status as a uniquely subtle theorist, whose writing will prove absorbing to academic and nonacademic readers alike.

The book considers the past accomplishments and future agendas of comparative-historical research in the social sciences. It defines the distinctiveness of this type of research and explores its strengths in explaining important outcomes (e.g. revolutions, social provision, democracy) in the world. It includes sections on substantive research accomplishments, methodology, and theory, and features essays by some of the most important political scientists and sociologists currently working.
This review of the accomplishments and future agendas of comparative historical research in the social sciences explores its strengths in explaining important worldwide outcomes (e.g., revolutions, social provision, democracy). It includes sections on substantive research accomplishments, methodology, and theory, and features essays by some of the most important political scientists and sociologists currently working.

In this comparative-historical analysis of Spanish America, Mahoney offers a new theory of colonialism and postcolonial development. He explores why certain kinds of societies are subject to certain kinds of colonialism and why these forms of colonialism give rise to countries with differing levels of economic prosperity and social well-being. Mahoney contends that differences in the extent of colonialism are best explained by the potentially evolving fit between the institutions of the colonizing nation and those of the colonized society. Moreover, he shows how institutions forged under colonialism bring countries to relative levels of development that may prove remarkably enduring in the postcolonial period. The argument is sure to stir discussion and debate, both among experts on Spanish America who believe that development is not tightly bound by the colonial past, and among scholars of colonialism who suggest that the institutional identity of the colonizing nation is of little consequence.

In treating memory as a cultural rather than an individual faculty, this book provides an account of how bodily practices are transmitted in, and as, traditions. Most studies of memory as a cultural faculty focus on written, or inscribed transmissions of memories. Paul Connerton, on the other hand, concentrates on bodily (or incorporated) practices, and so questions the currently dominant idea that literary texts may be taken as a metaphor for social practices generally. The author argues that images of the past and recollected knowledge of the past are conveyed and sustained by ritual performances and that performative memory is bodily. Bodily social memory is an essential aspect of social memory, but it is an aspect which has until now been badly neglected. An innovative study, this work should be of interest to researchers into social, political and anthropological thought as well as to graduate and undergraduate students.

This comparative historical sociology of the Bolshevik revolutionaries offers a reinterpretation of political radicalization in the last years of the Russian Empire. Finding that two-thirds of the Bolshevik leadership were ethnic minorities - Ukrainians, Latvians, Georgians, Jews and others - this book examines the shared experiences of assimilation and socioethnic exclusion that underlay their class universalism. It suggests that imperial policies toward the Empire's diversity radicalized class and ethnicity as intersectional experiences, creating an assimilated but excluded elite: lower-class Russians and middle-class minorities universalized particular exclusions as they disproportionately sustained the economic and political burdens of maintaining the multiethnic Russian Empire. The Bolsheviks' social identities and routes to revolutionary radicalism show especially how a class-universalist politics was appealing to those seeking secularism in response to religious tensions, a universalist politics where ethnic and geopolitical insecurities were exclusionary, and a tolerant 'imperial' imaginary where Russification and illiberal repressions were most keenly felt.

This book explores the Eurasian borderlands as contested 'shatter zones' which have generated some of the world's most significant conflicts. Analyzing the struggles of Habsburg, Russian, Ottoman, Iranian and Qing empires, Alfred J. Rieber surveys the period from the rise of the great multicultural, conquest empires in the late medieval/early modern period to their collapse in the early twentieth century. He charts how these empires expanded along moving, military frontiers, competing with one another in war, diplomacy and cultural practices, while the subjugated peoples of the borderlands strove to maintain their cultures and to defend their autonomy. The gradual and fragmentary adaptation of Western constitutional ideas, military reforms, cultural practices and economic penetration began to undermine these ruling ideologies and institutions, leading to the collapse of all five empires in revolution and war within little more than a decade between 1911 and 1923.

This innovative analysis investigates a complex issue of tremendous economic and political importance: what makes some countries vulnerable to banking crises, while others emerge unscathed? Banks on the Brink explains why some countries are more vulnerable to banking crises than others. Copelovitch and Singer highlight the effects of two variables in combination: foreign capital inflows and the relative prominence of securities markets in the domestic financial system. Foreign capital is the fuel for banks' potentially dangerous behavior, and banks are more likely to take on excessive risks when operating in a financial system with large securities markets. The book analyzes over thirty years of data and provides historical case studies of two key countries, Canada and Germany, each of which explores how political decisions in the 19th and early-20th centuries continue to affect financial stability today. The analyses in this book have crucial policy implications, identifying potential regulations and policies that can work to protect banking systems against future crises.
Stresses the under-explored relationship between banking systems, securities markets, and financial crises, illuminating the profound impact of factors on subsequent crises
Highlights the impact politics has on the development of a nation's financial markets, across space and time, in order to point out when and why banking systems become more prone to crisis
Uses comprehensive data analysis, in tandem with two historical case studies, Canada and Germany, in order to expand the study of financial crises beyond singular events and focus on enduring, institutional factors

For many applications, a randomized algorithm is either the simplest or the fastest algorithm available, and sometimes both. This book introduces the basic concepts in the design and analysis of randomized algorithms. The first part of the text presents basic tools such as probability theory and probabilistic analysis that are frequently used in algorithmic applications. Algorithmic examples are also given to illustrate the use of each tool in a concrete setting. In the second part of the book, each chapter focuses on an important area to which randomized algorithms can be applied, providing a comprehensive and representative selection of the algorithms that might be used in each of these areas. Although written primarily as a text for advanced undergraduates and graduate students, this book should also prove invaluable as a reference for professionals and researchers.

Class-tested and coherent, this groundbreaking new textbook teaches classic web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. Written from a computer science perspective by three leading experts in the field, it gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Although originally designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also create a buzz for researchers and professionals alike.
Contents
1. Information retrieval using the Boolean model; 2. The dictionary and postings lists; 3. Tolerant retrieval; 4. Index construction; 5. Index compression; 6. Scoring and term weighting; 7. Vector space retrieval; 8. Evaluation in information retrieval; 9. Relevance feedback and query expansion; 10. XML retrieval; 11. Probabilistic information retrieval; 12. Language models for information retrieval; 13. Text classification and Naive Bayes; 14. Vector space classification; 15. Support vector machines and kernel functions; 16. Flat clustering; 17. Hierarchical clustering; 18. Dimensionality reduction and latent semantic indexing; 19. Web search basics; 20. Web crawling and indexes; 21. Link analysis.
Reviews
“This is the first book that gives you a complete picture of the complications that arise in building a modern web-scale search engine. You'll learn about ranking SVMs, XML, DNS, and LSI. You'll discover the seedy underworld of spam, cloaking, and doorway pages. You'll see how MapReduce and other approaches to parallelism allow us to go beyond megabytes and to efficiently manage petabytes." -Peter Norvig, Director of Research, Google Inc.
"Introduction to Information Retrieval is a comprehensive, up-to-date, and well-written introduction to an increasingly important and rapidly growing area of computer science. Finally, there is a high-quality textbook for an area that was desperately in need of one." -Raymond J. Mooney, Professor of Computer Sciences, University of Texas at Austin
“Through compelling exposition and choice of topics, the authors vividly convey both the fundamental ideas and the rapidly expanding reach of information retrieval as a field.” -Jon Kleinberg, Professor of Computer Science, Cornell University

How can protests influence policymaking in a repressive dictatorship? Responsive Authoritarianism in China sheds light on this important question through case studies of land takings and demolitions - two of the most explosive issues in contemporary China. In the early 2000s, landless farmers and evictees unleashed waves of disruptive protests. Surprisingly, the Chinese government responded by adopting wide-ranging policy changes that addressed many of the protesters' grievances. Heurlin traces policy changes from local protests in the provinces to the halls of the National People's Congress (NPC) in Beijing. In doing so, he highlights the interplay between local protests, state institutions, and elite politics. He shows that the much-maligned petitioning system actually plays an important role in elevating protesters' concerns to the policymaking agenda. Delving deep into the policymaking process, the book illustrates how the State Council and NPC have become battlegrounds for conflicts between ministries and local governments over state policies.

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.

This book is a study of ancient views about 'moral luck'. It examines the fundamental ethical problem that many of the valued constituents of a well-lived life are vulnerable to factors outside a person's control, and asks how this affects our appraisal of persons and their lives. The Greeks made a profound contribution to these questions, yet neither the problems nor the Greek views of them have received the attention they deserve. This book thus recovers a central dimension of Greek thought and addresses major issues in contemporary ethical theory. One of its most original aspects is its interrelated treatment of both literary and philosophical texts. The Fragility of Goodness has proven to be important reading for philosophers and classicists, and its non-technical style makes it accessible to any educated person interested in the difficult problems it tackles. This new edition features an entirely new preface by Martha Nussbaum.

In this important new study Ian Hacking continues the enquiry into the origins and development of certain characteristic modes of contemporary thought undertaken in such previous works as his best selling Emergence of Probability. Professor Hacking shows how by the late nineteenth century it became possible to think of statistical patterns as explanatory in themselves, and to regard the world as not necessarily deterministic in character. Combining detailed scientific historical research with characteristic philosophic breath and verve, The Taming of Chance brings out the relations among philosophy, the physical sciences, mathematics and the development of social institutions, and provides a unique and authoritative analysis of the "probabilization" of the Western world.

Book Description
Historical records show that there was no real concept of probability in Europe before the mid-seventeenth century, although the use of dice and other randomizing objects was commonplace. Ian Hacking presents a philosophical critique of early ideas about probability, induction, and statistical inference and the growth of this new family of ideas in the fifteenth, sixteenth, and seventeenth centuries. The contemporary debates center around figures such as Pascal, Leibniz, and Jacques Bernoulli. Hacking invokes a wider intellectual framework involving the growth of science, economics, and the theology of the period. He argues that the transformations that made it possible for probability concepts to emerge have constrained all subsequent development of probability theory and determine the space within which philosophical debate on the subject is still conducted. First published in 1975, this edition includes a new introduction that contextualizes his book in light of new work and philosophical trends.

The second in the family of best-selling vocabulary reference and practice books from elementary to advanced level. Vocabulary is clearly presented and contextualized on left-hand pages with practice activities on facing right-hand pages. This book is primarily designed as a self-study reference and practice text but it can also be used for classroom work. This second edition has been fully revised to ensure that the vocabulary presented is current and relevant. It is beautifully illustrated in full colour and contains 100 units. This edition 'with answers' is ideal for self-study.

This authoritative translation by John Cottingham of the Meditations is taken from the much acclaimed three-volume Cambridge edition of the Philosophical Writings of Descartes. It is based on the best available texts and presents Descartes' central metaphysical writings in clear, readable modern English.

Statistical physics has its origins in attempts to describe the thermal properties of matter in terms of its constituent particles, and has played a fundamental role in the development of quantum mechanics. Based on lectures taught by Professor Kardar at MIT, this textbook introduces the central concepts and tools of statistical physics. It contains a chapter on probability and related issues such as the central limit theorem and information theory, and covers interacting particles, with an extensive description of the van der Waals equation and its derivation by mean field approximation. It also contains an integrated set of problems, with solutions to selected problems at the end of the book and a complete set of solutions is available to lecturers on a password protected website at www.cambridge.org/9780521873420. A companion volume, Statistical Physics of Fields, discusses non-mean field aspects of scaling and critical phenomena, through the perspective of renormalization group.

While many scientists are familiar with fractals, fewer are familiar with scale-invariance and universality which underly the ubiquity of their shapes. These properties may emerge from the collective behaviour of simple fundamental constituents, and are studied using statistical field theories. Initial chapters connect the particulate perspective developed in the companion volume, to the coarse grained statistical fields studied here. Based on lectures taught by Professor Kardar at MIT, this textbook demonstrates how such theories are formulated and studied. Perturbation theory, exact solutions, renormalization groups, and other tools are employed to demonstrate the emergence of scale invariance and universality, and the non-equilibrium dynamics of interfaces and directed paths in random media are discussed. Ideal for advanced graduate courses in statistical physics, it contains an integrated set of problems, with solutions to selected problems at the end of the book and a complete set available to lecturers at www.cambridge.org/9780521873413.