The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming content through social media. Understanding and processing this new type of data to glean actionable patterns presents challenges and opportunities for interdisciplinary research, novel algorithms, and tool development. Social Media Mining integrates social media, social network analysis, and data mining to provide a convenient and coherent platform for students, practitioners, researchers, and project managers to understand the basics and potentials of social media mining. It introduces the unique problems arising from social media data and presents fundamental concepts, emerging issues, and effective algorithms for network analysis and data mining. Suitable for use in advanced undergraduate and beginning graduate courses as well as professional short courses, the text contains exercises of different degrees of difficulty that improve understanding and help apply concepts, principles, and methods in various scenarios of social media mining.

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric convergence analysis and numerical stability analysis to complete the first and definitive treatment of the entire framework of density ratio estimation in machine learning.

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.

Book description
High-dimensional data appear in many fields, and their analysis has become increasingly important in modern statistics. However, it has long been observed that several well-known methods in multivariate analysis become inefficient, or even misleading, when the data dimension p is larger than, say, several tens. A seminal example is the well-known inefficiency of Hotelling's T2-test in such cases. This example shows that classical large sample limits may no longer hold for high-dimensional data; statisticians must seek new limiting theorems in these instances. Thus, the theory of random matrices (RMT) serves as a much-needed and welcome alternative framework. Based on the authors' own research, this book provides a firsthand introduction to new high-dimensional statistical methods derived from RMT. The book begins with a detailed introduction to useful tools from RMT, and then presents a series of high-dimensional problems with solutions provided by RMT methods.
Reviews
'This is the first book which treats systematic corrections to the classical multivariate statistical procedures so that the resultant procedures can be used for high-dimensional data. The corrections have been done by employing asymptotic tools based on the theory of random matrices.'
Yasunori Fujikoshi - Hiroshima University, Japan
'… this book is the first to cover these topics and can serve both as a good introduction to the topics as well as a comprehensive reference on the state of the art.'
Robert Stelzer Source: MathSciNet
'This book deals with the analysis of covariance matrices under two different assumptions: large-sample theory and high-dimensional-data theory. While the former approach is the classical framework to derive asymptotics, nevertheless the latter has received increasing attention due to its applications in the emerging field of big-data. Due to its novelty and its relevance in the current research, the authors focus mainly on the high-dimensional-data framework. … The theory and the applications are presented under both the large-sample theory and the high-dimensional-data theory, and thus the reader can easily appreciate the differences between the two approaches. The material is presented in a quite simple manner, and the reader only needs some pre-requisites in basic mathematical statistics, linear algebra, and theory of multivariate normal distributions. Some technical prerequisites are collected in two appendices. Therefore, the book can be used by graduate students and researchers in a wide range of disciplines, ranging from mathematics to applied sciences.'
Fabio Rapallo Source: Zentralblatt MATH

Details the evolution of the monetary standard from the start of the Federal Reserve through the end of the Greenspan era. The book places that evolution in the context of the intellectual and political environment of the time. By understanding the fitful process of replacing a gold standard with a paper money standard, the conduct of monetary policy becomes a series of experiments useful for understanding the fundamental issues concerning money and prices. How did the recurrent monetary instability of the 20th century relate to the economic instability and to the associated political and social turbulence? After the detour in policy represented by FOMC chairmen Arthur Burns and G. William Miller, Paul Volcker and Alan Greenspan established the monetary standard originally foreshadowed by William McChesney Martin, who became chairman in 1951. The Monetary Policy of the Federal Reserve explains in a straightforward way the emergence and nature of the modern, inflation-targeting central bank.

Encourage students to reflect on the processes of thinking, as well as practising thinking skills. Thinking Skills encourages students to reflect on the processes of thinking, as well as developing and practising thinking skills. It is divided into two sections: Critical thinking and Problem solving. As well as giving students a thorough grounding in these areas, the authors provide opportunities for students to analyse and evaluate arguments, analyse numerical and graphical information and develop a range of skills.

This is a comprehensive account of the semantics and the implementation of the whole Lisp family of languages, namely Lisp, Scheme and related dialects. It describes 11 interpreters and 2 compilers, including very recent techniques of interpretation and compilation. The book is in two parts. The first starts from a simple evaluation function and enriches it with multiple name spaces, continuations and side-effects with commented variants, while at the same time the language used to define these features is reduced to a simple lambda-calculus. Denotational semantics is then naturally introduced. The second part focuses more on implementation techniques and discusses precompilation for fast interpretation: threaded code or bytecode; compilation towards C. Some extensions are also described such as dynamic evaluation, reflection, macros and objects. This will become the new standard reference for people wanting to know more about the Lisp family of languages: how they work, how they are implemented, what their variants are and why such variants exist. The full code is supplied (and also available over the Net). A large bibliography is given as well as a considerable number of exercises. Thus it may also be used by students to accompany second courses on Lisp or Scheme.

Analytic combinatorics aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the analysis of algorithms and for the study of scientific models in many disciplines, including probability theory, statistical physics, computational biology, and information theory. With a careful combination of symbolic enumeration methods and complex analysis, drawing heavily on generating functions, results of sweeping generality emerge that can be applied in particular to fundamental structures such as permutations, sequences, strings, walks, paths, trees, graphs and maps. This account is the definitive treatment of the topic. The authors give full coverage of the underlying mathematics and a thorough treatment of both classical and modern applications of the theory. The text is complemented with exercises, examples, appendices and notes to aid understanding. The book can be used for an advanced undergraduate or a graduate course, or for self-study.

This is the newly revised and expanded edition of the popular introduction to the design and implementation of geometry algorithms arising in areas such as computer graphics, robotics, and engineering design. The second edition contains material on several new topics, such as randomized algorithms for polygon triangulation, planar point location, 3D convex hull construction, intersection algorithms for ray-segment and ray-triangle, and point-in-polyhedron. A new "Sources" chapter points to supplemental literature for readers needing more information on any topic. A novel aspect is the inclusion of working C code for many of the algorithms, with discussion of practical implementation issues. The self-contained treatment presumes only an elementary knowledge of mathematics, but reaches topics on the frontier of current research, making it a useful reference for practitioners at all levels. The code in this new edition is significantly improved from the first edition, and four new routines are included. Java versions for this new edition are also available. All code is accessible from the book's Web site (http://cs.smith.edu/~orourke/) or by anonymous ftp.

A two-volume study of political thought from the late thirteenth to the end of the sixteenth century, the decisive period of transition from medieval to modern political theory. The work is intended to be both an introduction to the period for students, and a presentation and justification of a particular approach to the interpretation of historical texts. Quentin Skinner gives an outline account of all the principal texts of the period, discussing in turn the chief political writings of Dante, Marsiglio, Bartolus, Machiavelli, Erasmus and more, Luther and Calvin, Bodin and the Calvinist revolutionaries. But he also examines a very large number of lesser writers in order to explain the general social and intellectual context in which these leading theorists worked. He thus presents the history not as a procession of 'classic texts' but are more readily intelligible. He traces by this means the gradual emergence of the vocabulary of modern political thought, and in particular the crucial concept of the State. We are given an insight into the actual processes of the formation of ideologies and into some of the linkages between political theory and practice. Professor Skinner has been awarded the Balzan Prize Life Time Achievement Award for Political Thought, History and Theory. Full details of this award can be found at http://www.balzan.it/News_eng.aspx?ID=2474

Nobel laureate Erwin Schrödinger's What is Life? is one of the great science classics of the twentieth century. The philosopher Karl Popper hailed it as a 'beautiful and important book' by 'a great man to whom I owe a personal debt for many exciting discussions'.

'Publish or perish' is a well-established adage in academia. Never has the pressure on academics to publish been greater. Yet the prospect of writing a book can seem daunting, while the business of getting it published may be mystifying. Written by an expert in academic publishing, Writing Successful Academic Books provides a practical guide to both writing and getting published. It covers all stages of academic authorship from developing the initial idea for a book through to post-publication issues, showing how to avoid the common pitfalls and achieve academic and professional success through publication. Full of real life examples, including a sample book proposal, the book covers everything you need to know to build up an authorial career. This is an invaluable guide for academic authors - prospective or established - in all disciplines.

This engaging 2005 introduction offers a critical approach to discourse, written by an expert uniquely placed to cover the subject for a variety of disciplines. Organised along thematic lines, the book begins with an outline of the basic principles, moving on to examine the methods and theory of CDA (critical discourse analysis). It covers topics such as text and context, language and inequality, choice and determination, history and process, ideology and identity. Blommaert focuses on how language can offer a crucial understanding of wider aspects of power relations, arguing that critical discourse analysis should specifically be an analysis of the 'effects' of power, what power does to people, groups and societies, and how this impact comes about. Clearly argued, this concise introduction will be welcomed by students and researchers in a variety of disciplines involved in the study of discourse, including linguistics, linguistic anthropology and the sociology of language.

The Bildungsroman--the story of the development or formation of a young man--is the most famous German contribution to the European novel. In this study Michael Minden offers detailed readings of some of the best-known novels in the German language, from Goethe's Wilhelm Meisters Lehrjahre to Mann's Der Zauberberg. Taking account of contemporary literary theory, Minden uncovers aspects and motifs that subvert traditional ideas of the Bildungsroman, and raise questions about the function and status of literature.