Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. This book can be used for readers who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.

    Johnson. It was the first book exclusively on the theory of NP-completeness and computational intractability. The book features an appendix providing a thorough compendium of NP-complete problems (which was updated in later printings of the book). The book is now outdated in some respects as it does not cover more recent development such as the PCP theorem. It is nevertheless still in print and is regarded as a classic: in a 2006 study, the CiteSeer search engine listed the book as the most cited reference in computer science literature.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    It offers a comprehensive and accessible treatment of the theory of algorithms and complexity—the elegant body of concepts and methods developed by computer scientists over the past 30 years for studying the performance and limitations of computer algorithms. The book is self-contained in that it develops all necessary mathematical prerequisites from such diverse fields such as computability, logic, number theory and probability.

    Presents essential ideas on critical phenomena developed over the last decade in simple, qualitative terms. This new edition maintains the simple structure of the first and puts new emphasis on pedagogical considerations. Thermostatistics is incorporated into the text without eclipsing macroscopic thermodynamics, and is integrated into the conceptual framework of physical theory.

    With an emphasis on critical self-reflection, Reflect & Relate gives students the practical skills to work through life's many challenges using better interpersonal communication. The sound theory, clear explanations, lively writing, practical activities, and vibrant design all work toward a single goal: Teaching students to make better communication choices so they can build happier and healthier interpersonal relationships.

    Taking as a starting point a drawing he made in Medellin in 2006—as well as its caption, “I swear I saw this”—Taussig considers the fieldwork notebook as a type of modernist literature and the place where writers and other creators first work out the imaginative logic of discovery. Notebooks mix the raw material of observation with reverie, juxtaposed, in Taussig’s case, with drawings, watercolors, and newspaper cuttings, which blend the inner and outer worlds in a fashion reminiscent of Brion Gysin and William Burroughs’s surreal cut-up technique. Focusing on the small details and observations that are lost when writers convert their notes into finished pieces, Taussig calls for new ways of seeing and using the notebook as form. Memory emerges as a central motif in I Swear I Saw This as he explores his penchant to inscribe new recollections in the margins or directly over the original entries days or weeks after an event. This palimpsest of afterthoughts leads to ruminations on Freud’s analysis of dreams, Proust’s thoughts on the involuntary workings of memory, and Benjamin’s theories of history—fieldwork, Taussig writes, provokes childhood memories with startling ease. I Swear I Saw This exhibits Taussig’s characteristic verve and intellectual audacity, here combined with a revelatory sense of intimacy. He writes, “drawing is thus a depicting, a hauling, an unraveling, and being impelled toward something or somebody.” Readers will exult in joining Taussig once again as he follows the threads of a tangled skein of inspired associations.

    Initially conceptualized as a survival guide for children, teens, young adults and parents; it quickly transcended into this unprecedented, critical volume. This encompassing work responds to the many desperate and heartbreaking pleas of those affected by dysautonomia; included are clear explanations of medical information, evidenced-based research, best practices for clinical diagnoses and treatment options, alternative/complimentary medicine approaches, non-medical strategies, coping techniques, helpful tips, patient rights and options, and inspiring narrative accounts of people living with the syndrome around the globe. The book contributors and its readers join hand in hand to represent the POTS dysautonomia community's shared struggles and hopes, concerns and endeavors, unequivocally serving as a living testament that "Together We Stand." This is the 3rd Edition!

    Hermann Weyl explores the concept of symmetry beginning with the idea that it represents a harmony of proportions, and gradually departs to examine its more abstract varieties and manifestations--as bilateral, translatory, rotational, ornamental, and crystallographic. Weyl investigates the general abstract mathematical idea underlying all these special forms, using a wealth of illustrations as support. Symmetry is a work of seminal relevance that explores the great variety of applications and importance of symmetry.

    This book includes discussions which aid in student understanding of theoretical material through the use of specific cases. It is suitable for undergraduate Mechanics course.

    Despite its relatively narrow focus, it is chock full of the pearls of clinical wisdom that students and practitioners treasure, and many of these lessons apply to medicine in general. The book was well characterized by a reviewer of an earlier edition for The New England Journal of Medicine: If only one book about surgery could be made available to physicians from all specialties, it should probably be Silen's recent revision of Cope's Early Diagnosis of the Acute Abdomen. Since the book first appeared more than 30 years ago, it has remained the classic treatise on the initial approach to abdominal pain. Because acute, severe abdominal pain is still a common problem whose misdiagnosis can result in quick death, each generation of beginning physicians is faced with the urgency of learning to make a diagnosis in this high anxiety situation and they appreciate the wise, humane, precisely detailed guidance offered by Cope and Silen. For the 21st Edition, Dr. Silen has again updated the text in a respectful but significant way. He has strengthened its emphasis on pitfalls in the interpretation of CT and ultrasound scans, on misadventures caused by over-reliance on blood tests and radiographs, and on careful history-taking to avoid the costs of inappropriate lab tests. He has also reviewed the data from a randomized clinical trial indicating that patients should receive adequate analgesia while awaiting a definitive diagnosis, a dictum that is contrary to traditional teaching

    Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory.All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points.The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated referencesNow current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.

    You have arrived in the hills. In here, you are surrounded by dense, menacing forests, enveloped in a deadly silence... You never know what lurks here in the Cold, dark night. Do not walk alone after sunset in the hills. A beautiful woman in white haunts the Lonely pathways, looking to enchant and ensnare men... All the people who died in accidents here... They say you hear their screams at night. And the deserted lodges sitting amidst lush greenery and calm streams... Spirits lie in wait here, ready to prey on the living. There are sceptics who did not heed these warnings. They tried to rationalize what they saw, what they felt. But when they came face to face with the beings that they believed didn’t exist, they couldn’t run away anymore... Ghosts of the silent hills is a collection that will make your nights a little scarier, encompassing the very best spine-chilling stories based on true hauntings.About the AuthorBorn in Shimla in 1955, Anita Krishan spent the initial twenty-two years of her life in this pristine Himalayan town, earning her master’s degree in English literature from Himachal University, and moving on to a career of introducing delights of the language to her young learners. In her long tenure as an educator, she has enriched the lives of countless students with the mystery of the narrative. A versatile writer, each of her literary works appertains to a different genre... from the joys and travails of life, to terrorism that has brought the world to its tenterhooks, to now the paranormal. She has travelled extensively around the globe absorbing the diverse human ethos and cultures—the delectable food for her thoughts. Presently, she lives in Gurgaon with her family.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.