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Sructure of Antigens
Structure of Antigens discusses a variety of topics dealing with the structural basis of antigenicity. Topics include the analytical methods used to elucidate the structure of antigens, the structure of antibodies, the principles underlying modern immunoassays and the measurement of antibody binding affinity, and physicochemical principles and methodological aspects. The book also considers major groups of antigens distinguished by their functional activity and biological role (e.g., drugs, autoantigens, snake toxins, allergens) or by their association with particular biological systems (e.g., antigens of microorganisms). Structure of Antigens will provide a current, useful, reference for researchers and graduate students in all fields of biological science who need an overview of antigenic specificity. VOLUME 1
Markov Decision Processes
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This text is unique in bringing together so many results hitherto found only in part in other texts and papers. . . . The text is fairly self-contained, inclusive of some basic mathematical results needed, and provides a rich diet of examples, applications, and exercises. The bibliographical material at the end of each chapter i...
Elam
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ECAI 2010
LC copy bound in 2 v.: v. 1, p. 1-509; v. 2, p. [509]-1153.
High Performance Computing
This book constitutes the proceedings of the 4th Latin American Conference on High Performance Computing, CARLA 2017, held in Buenos Aires, Argentina, and Colonia del Sacramento, Uruguay, in September 2017. The 29 papers presented in this volume were carefully reviewed and selected from 50 submissions. They are organized in topical sections named: HPC infrastructures and datacenters; HPC industry and education; GPU, multicores, accelerators; HPC applications and tools; big data and data management; parallel and distributed algorithms; Grid, cloud and federations.
Mycobacterium tuberculosis
Tuberculosis once again occupies a special position in the areas of infec tious diseases and microbiology. This disease has been important to mankind since even before biblical times. Tuberculosis has been a major cause of morbidity and mortality in humans, especially in highly ur banized Europe, until a few decades ago. Indeed, this disease became a center of many novels, plays, and operas, since it appeared to be quite popular to have the heroine dying of "consumption. " Most importantly, tuberculosis also became the focus of attention for many investigations during the 19th and even the 20th centuries. Major advances were made in the areas of isolation and identification of M. tuberculosi...
Lifelong Machine Learning
Lifelong Machine Learning (or Lifelong Learning) is an advanced machine learning paradigm that learns continuously, accumulates the knowledge learned in previous tasks, and uses it to help future learning. In the process, the learner becomes more and more knowledgeable and effective at learning. This learning ability is one of the hallmarks of human intelligence. However, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model. It makes no attempt to retain the learned knowledge and use it in future learning. Although this isolated learning paradigm has been very successful, it requir...
Statistics for Machine Learning
Build Machine Learning models with a sound statistical understanding. About This Book Learn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics. Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering. Master the statistical aspect of Machine Learning with the help of this example-rich guide to R and Python. Who This Book Is For This book is intended for developers with little to no background in statistics, who want to implement Machine Learning in their systems. Some programming knowledge in R or Python will be useful. What You Will Learn Understand the Statistical and Machine Learning...
