This book constitutes the refereed proceedings of the 17th Annual Conference on Learning Theory, COLT 2004, held in Banff, Canada in July 2004. The 46 revised full papers presented were carefully reviewed and selected from a total of 113 submissions. The papers are organized in topical sections on economics and game theory, online learning, inductive inference, probabilistic models, Boolean function learning, empirical processes, MDL, generalisation, clustering and distributed learning, boosting, kernels and probabilities, kernels and kernel matrices, and open problems.
This book constitutes the refereed proceedings of the 7th International Conference on Intelligent Data Analysis, IDA 2007, held in Ljubljana, Slovenia. The 33 revised papers were carefully reviewed and selected from almost 100 submissions. The book covers all current aspects of this interdisciplinary field, including statistics, machine learning, data mining, classification and pattern recognition, clustering, applications, modeling, and interactive dynamic data visualization.
This is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software ensure that it forms an ideal starting point for further study. Equally, the book and its associated web site will guide practitioners to updated literature, new applications, and on-line software.
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is focused on the development and implementation of statistically motivated, data-driven techniques for digital image analysis of remotely sensed imagery and it features a tight interweaving of statistical and machine learning theory of algorithms with computer codes. It develops statistical methods for the analysis of optical/infrared and synthetic aperture radar (SAR) imagery, including wavelet transformations, kernel methods for nonlinear classification, as well as an introduction to deep learning in the context of feed forward neural networks. New in the Fourth Edition: An in-depth treatment of a recent sequential change detection algorithm for polarimetric SAR image time series. The accompanying software consists of Python (open source) versions of all of the main image analysis algorithms. Presents easy, platform-independent software installation methods (Docker containerization). Utilizes freely accessible imagery via the Google Earth Engine and provides many examples of cloud programming (Google Earth Engine API). Examines deep learning examples including TensorFlow and a sound introduction to neural networks, Based on the success and the reputation of the previous editions and compared to other textbooks in the market, Professor Canty’s fourth edition differs in the depth and sophistication of the material treated as well as in its consistent use of computer codes to illustrate the methods and algorithms discussed. It is self-contained and illustrated with many programming examples, all of which can be conveniently run in a web browser. Each chapter concludes with exercises complementing or extending the material in the text.
William Alwyn: A Research and Information Guide is a catalogue, discography and annotated bibliography of the nearly 500 works of this twentieth-century British composer. It will be invaluable to twentieth-century British composer researchers and aficionados, music history courses, and film music courses.
The first edition, by the late Edward Malins, of this informative guide to the life and works of one of the most important and difficult poets of the 20th century, has now been extensively revised by John Purkis. It begins by providing biographical details on Yeats, with particular emphasis on his education, his appearance and his characteristics. It then places the poet in his cultural background, discussing the history of Ireland and major ideas which influenced his poetry. This is followed by an updated critical section which includes careful close readings of ten of his poems. The book concludes with an extensive reference section containing information about his many friends and their influence on and connection with particular poems.
Summary Practical Data Science with R, Second Edition takes a practice-oriented approach to explaining basic principles in the ever expanding field of data science. You’ll jump right to real-world use cases as you apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support. About the technology Evidence-based decisions are crucial to success. Applying the right data analysis techniques to your carefully curated business data helps you make accurate predictions, identify trends, and spot trouble in advance. The R data analysis platform provides the tools you need to tackle day-to-day data analysis and machine learning tasks efficiently and effectively. About the book Practical Data Science with R, Second Edition is a task-based tutorial that leads readers through dozens of useful, data analysis practices using the R language. By concentrating on the most important tasks you’ll face on the job, this friendly guide is comfortable both for business analysts and data scientists. Because data is only useful if it can be understood, you’ll also find fantastic tips for organizing and presenting data in tables, as well as snappy visualizations. What's inside Statistical analysis for business pros Effective data presentation The most useful R tools Interpreting complicated predictive models About the reader You’ll need to be comfortable with basic statistics and have an introductory knowledge of R or another high-level programming language. About the author Nina Zumel and John Mount founded a San Francisco–based data science consulting firm. Both hold PhDs from Carnegie Mellon University and blog on statistics, probability, and computer science.
This book fully describes the purpose, methods, and implementation of clinical audit programs in mental health care in order to meet the demands of purchasers, providers, clinicians, carers and patients. It provides a practical guide to implementation in hospital and community settings. Applies well-established models for clinical audit to mental health care. Reflects current trends in quality assurance in health care. Provides detailed, specific advice on assessing the effectiveness of mental health treatment programs.
Studies of Irish fiction are still scanty in contrast to studies of Irish poetry and drama. Attempting to fill a large critical vacancy, Irish Novels 1890-1940 is a comprehensive survey of popular and minor fiction (mainly novels) published between 1890 and 1922, a crucial period in Irish cultural and political history. Since the bulk of these sixty-odd writers have never been written about, certainly beyond brief mentions, the book opens up for further exploration a literary landscape, hitherto neglected, perhaps even unsuspected. This new landscape should alter the familiar perspectives on Irish literature of the period, first of all by adding genre fiction (science fiction, detective novels, ghost stories, New Woman fiction, and Great War novels) to the Irish syllabus, secondly by demonstrating the immense contribution of women writers to popular and mainstream Irish fiction. Among the popular and prolific female writers discussed are Mrs J.H. Riddell, B.M. Croker, M.E. Francis, Sarah Grand, Katharine Tynan, Ella MacMahon, Katherine Cecil Thurston, W.M. Letts, and Hannah Lynch. Indeed, a critical inference of the survey is that if there is a discernible tradition of the Irish novel, it is largely a female tradition. A substantial postscript surveys novels by Irish women between 1922 and1940 and relates them to the work of their female antecedents. This ground-breaking survey should also alter the familiar perspectives on the Ireland of 1890-1922. Many of the popular works were problem-novels and hence throw light on contemporary thinking and debate on the 'Irish Question'. After the Irish Literary Revival and creation of the Free State, much popular and mainstream fiction became a lost archive, neglected evidence, indeed, of a lost Ireland.
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