Outlier States examines the role of the United States as an enforcer against the development of nuclear weapons in the international community. In the Bush era Iran and North Korea were branded “rogue” states for their flouting of international norms, and changing their regimes was the administration’s goal. The Obama administration has chosen instead to call the countries nuclear “outliers” and has proposed means other than regime change to bring them back into “the community of nations.” Outlier States, the successor to Litwak’s influential Regime Change: U.S. Strategy through the Prism of 9/11 (2007), explores this significant policy adjustment and raises questions about its feasibility and its possible consequences. Do international norms apply only to states’ external behavior, as it might relate, for example, to nuclear proliferation and terrorism, or do they matter no less for states’ internal behavior, as it might affect a population’s human rights? What is the appropriate role for the United States in the process of reintegration? America’s military power remains unmatched, but can the nation any longer shape singlehandedly an increasingly multi-polar international system? What do the precedents set in Iraq and Libya teach us about how current outliers can be integrated into the international community? And perhaps most important, how should the United States respond if outlier regimes eschew integration as a threat to their survival and continue to augment their nuclear capabilities?

Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time series-based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types including high-dimensional data, uncertain data, stream data, network data, time series data, spatial data, and spatio-temporal data. While there have been many tutorials and surveys for general outlier detection, we focus on outlier detection for temporal data in this book. A large number of applications generate temporal datasets. For example, in our everyday life, various kinds of records like credit, personnel, financial, judicial, medical, etc., are all temporal. This stresses the need for an organized and detailed study of outliers with respect to such temporal data. In the past decade, there has been a lot of research on various forms of temporal data including consecutive data snapshots, series of data snapshots and data streams. Besides the initial work on time series, researchers have focused on rich forms of data including multiple data streams, spatio-temporal data, network data, community distribution data, etc. Compared to general outlier detection, techniques for temporal outlier detection are very different. In this book, we will present an organized picture of both recent and past research in temporal outlier detection. We start with the basics and then ramp up the reader to the main ideas in state-of-the-art outlier detection techniques. We motivate the importance of temporal outlier detection and brief the challenges beyond usual outlier detection. Then, we list down a taxonomy of proposed techniques for temporal outlier detection. Such techniques broadly include statistical techniques (like AR models, Markov models, histograms, neural networks), distance- and density-based approaches, grouping-based approaches (clustering, community detection), network-based approaches, and spatio-temporal outlier detection approaches. We summarize by presenting a wide collection of applications where temporal outlier detection techniques have been applied to discover interesting outliers. Table of Contents: Preface / Acknowledgments / Figure Credits / Introduction and Challenges / Outlier Detection for Time Series and Data Sequences / Outlier Detection for Data Streams / Outlier Detection for Distributed Data Streams / Outlier Detection for Spatio-Temporal Data / Outlier Detection for Temporal Network Data / Applications of Outlier Detection for Temporal Data / Conclusions and Research Directions / Bibliography / Authors' Biographies

The problem of outliers is one of the oldest in statistics, and during the last century and a half interest in it has waxed and waned several times. Currently it is once again an active research area after some years of relative neglect, and recent work has solved a number of old problems in outlier theory, and identified new ones. The major results are, however, scattered amongst many journal articles, and for some time there has been a clear need to bring them together in one place. That was the original intention of this monograph: but during execution it became clear that the existing theory of outliers was deficient in several areas, and so the monograph also contains a number of new results and conjectures. In view of the enormous volume ofliterature on the outlier problem and its cousins, no attempt has been made to make the coverage exhaustive. The material is concerned almost entirely with the use of outlier tests that are known (or may reasonably be expected) to be optimal in some way. Such topics as robust estimation are largely ignored, being covered more adequately in other sources. The numerous ad hoc statistics proposed in the early work on the grounds of intuitive appeal or computational simplicity also are not discussed in any detail.

This book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appeals to multiple communities. The chapters of this book can be organized into three categories: Basic algorithms: Chapters 1 through 7 discuss the fundamental algorithms for outlier analysis, including probabilistic and statistical methods, linear methods, proximity-based methods, high-dimensional (subspace) methods, ensemble methods, and supervised methods. Domain-specific methods: Chapters 8 through 12 discuss outlier detection algorithms for various domains of data, such as text, categorical data, time-series data, discrete sequence data, spatial data, and network data. Applications: Chapter 13 is devoted to various applications of outlier analysis. Some guidance is also provided for the practitioner. The second edition of this book is more detailed and is written to appeal to both researchers and practitioners. Significant new material has been added on topics such as kernel methods, one-class support-vector machines, matrix factorization, neural networks, outlier ensembles, time-series methods, and subspace methods. It is written as a textbook and can be used for classroom teaching.

Can international institutions help create more cooperative and peaceful relations between states? If so, how? And what motivates states to create meaningful institutions in the first place? Though theorists and researchers have approached these questions from different schools of thought, the commonality among them is that institutions are apolitical and their purpose is to assure common gains or develop shared social norms and identities. Institutions succeed if they rise above petty power politics and fail when they succumb to political confrontations. In this book, Erik Voeten offers a new broader understanding of international institutions. Current theories offer conflicting portraits of why IOs form, why the succeed (or not) and their role in current politics. While international institutions can enhance the welfare of participants, they are simultaneously the structural means through which actors try to get what they want, often at the expense of others. Voeten argues that these distributive politics shape institutions and, in turn, institutions shape the conduct of such politics. The book will largely be theoretical, as its purpose is to illustrate an alternative way of understanding institutions rather than to test a specific hypothesis. After developing what the distributive theory of international institutions is, Voeten examines how this theory bears on other understandings of international institutions on a variety of scholarly perspectives, drawing on the extensive work in this area

Statistics: Unlocking the Power of Data, 2nd Edition continues to utilize these intuitive methods like randomization and bootstrap intervals to introduce the fundamental idea of statistical inference. These methods are brought to life through authentically relevant examples, enabled through easy to use statistical software, and are accessible at very early stages of a course. The program includes the more traditional methods like t-tests, chi-square texts, etc. but only after students have developed a strong intuitive understanding of inference through randomization methods. The focus throughout is on data analysis and the primary goal is to enable students to effectively collect data, analyze data, and interpret conclusions drawn from data. The program is driven by real data and real applications.

“Important . . . [a] landmark presidential biography . . . Bird is able to build a persuasive case that the Carter presidency deserves this new look.”—The New York Times Book Review An essential re-evaluation of the complex triumphs and tragedies of Jimmy Carter’s presidential legacy—from the expert biographer and Pulitzer Prize–winning co-author of American Prometheus Four decades after Ronald Reagan’s landslide win in 1980, Jimmy Carter’s one-term presidency is often labeled a failure; indeed, many Americans view Carter as the only ex-president to have used the White House as a stepping-stone to greater achievements. But in retrospect the Carter political odyssey is a rich and human story, marked by both formidable accomplishments and painful political adversity. In this deeply researched, brilliantly written account, Pulitzer Prize–winning biographer Kai Bird deftly unfolds the Carter saga as a tragic tipping point in American history. As president, Carter was not merely an outsider; he was an outlier. He was the only president in a century to grow up in the heart of the Deep South, and his born-again Christianity made him the most openly religious president in memory. This outlier brought to the White House a rare mix of humility, candor, and unnerving self-confidence that neither Washington nor America was ready to embrace. Decades before today’s public reckoning with the vast gulf between America’s ethos and its actions, Carter looked out on a nation torn by race and demoralized by Watergate and Vietnam and prescribed a radical self-examination from which voters recoiled. The cost of his unshakable belief in doing the right thing would be losing his re-election bid—and witnessing the ascendance of Reagan. In these remarkable pages, Bird traces the arc of Carter’s administration, from his aggressive domestic agenda to his controversial foreign policy record, taking readers inside the Oval Office and through Carter’s battles with both a political establishment and a Washington press corps that proved as adversarial as any foreign power. Bird shows how issues still hotly debated today—from national health care to growing inequality and racism to the Israeli-Palestinian conflict—burned at the heart of Carter’s America, and consumed a president who found a moral duty in solving them. Drawing on interviews with Carter and members of his administration and recently declassified documents, Bird delivers a profound, clear-eyed evaluation of a leader whose legacy has been deeply misunderstood. The Outlier is the definitive account of an enigmatic presidency—both as it really happened and as it is remembered in the American consciousness.