Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Автор: Pasquale Foggia; Cheng-Lin Liu; Mario Vento Название: Graph-Based Representations in Pattern Recognition ISBN: 3319589601 ISBN-13(EAN): 9783319589602 Издательство: Springer Рейтинг: Цена: 6707.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The papers discuss research results and applications in the intersection of pattern recognition, image analysis, graph theory, and also the application of graphs to pattern recognition problems in other fields like computational topology, graphic recognition systems and bioinformatics.
Автор: Cheng-Lin Liu; Bin Luo; Walter G. Kropatsch; Jian Название: Graph-Based Representations in Pattern Recognition ISBN: 3319182234 ISBN-13(EAN): 9783319182230 Издательство: Springer Рейтинг: Цена: 6830.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The accepted papers cover diverse issues of graph-based methods and applications, with 7 in graph representation,15 in graph matching, 7 in graph clustering and classification, and 7 in graph-based applications.
Автор: Jean-Michel Jolion; Walter Kropatsch Название: Graph Based Representations in Pattern Recognition ISBN: 3211831215 ISBN-13(EAN): 9783211831212 Издательство: Springer Рейтинг: Цена: 10610.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Graph-based representation of images represents in a compact way the structure of a scene to be analyzed and allows for an easy manipulation of sub-parts or of relationships between parts. This book groups 14 papers in the subject areas of: hypergraphs, recognition, detection, matching, segmentation, implementation problems and representation.
Автор: Walter Kropatsch; Nicole M. Artner; Yll Haxhimusa; Название: Graph-Based Representations in Pattern Recognition ISBN: 3642382207 ISBN-13(EAN): 9783642382208 Издательство: Springer Рейтинг: Цена: 5611.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 9th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2013, held in Vienna, Austria, in May 2013. They are organized in topical sections named: finding subregions in graphs; graph representations, segmentation and shape; and search in graphs.
Автор: Andrea Torsello; Francisco Escolano Ruiz; Luc Brun Название: Graph-Based Representations in Pattern Recognition ISBN: 3642021239 ISBN-13(EAN): 9783642021237 Издательство: Springer Рейтинг: Цена: 9146.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2009, held in Venice, Italy in May 2009.
Автор: Shalev-Shwartz Название: Understanding Machine Learning ISBN: 1107057132 ISBN-13(EAN): 9781107057135 Издательство: Cambridge Academ Рейтинг: Цена: 11194.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. This book explains the principles behind the automated learning approach and the considerations underlying its usage. The authors explain the `hows` and `whys` of machine-learning algorithms, making the field accessible to both students and practitioners.
Описание: A common feature of many approaches to modeling sensory statistics is an emphasis on capturing the ""average."" From early representations in the brain, to highly abstracted class categories in machine learning for classification tasks, central-tendency models based on the Gaussian distribution are a seemingly natural and obvious choice for modeling sensory data. However, insights from neuroscience, psychology, and computer vision suggest an alternate strategy: preferentially focusing representational resources on the extremes of the distribution of sensory inputs. The notion of treating extrema near a decision boundary as features is not necessarily new, but a comprehensive statistical theory of recognition based on extrema is only now just emerging in the computer vision literature. This book begins by introducing the statistical Extreme Value Theory (EVT) for visual recognition. In contrast to central-tendency modeling, it is hypothesized that distributions near decision boundaries form a more powerful model for recognition tasks by focusing coding resources on data that are arguably the most diagnostic features. EVT has several important properties: strong statistical grounding, better modeling accuracy near decision boundaries than Gaussian modeling, the ability to model asymmetric decision boundaries, and accurate prediction of the probability of an event beyond our experience. The second part of the book uses the theory to describe a new class of machine learning algorithms for decision making that are a measurable advance beyond the state-of-the-art. This includes methods for post-recognition score analysis, information fusion, multi-attribute spaces, and calibration of supervised machine learning algorithms.
Описание: This book constitutes the refereed proceedings of the 7th International Workshop on Representations, Analysis and Recognition of Shape and Motion from Imaging Data, RFMI 2017, held in Savoi, France, in December 2017.
The 8 revised full papers and 9 revised short papers presented were carefully reviewed and selected from 23 submissions. The papers are organized in topical sections on analyzing motion data; deep learning on image and shape data; 2D and 3D pattern classification; watermarking, segmentation and deformations.
Автор: Bishop, Christopher M. Название: Neural Networks for Pattern Recognition ISBN: 0198538642 ISBN-13(EAN): 9780198538646 Издательство: Oxford Academ Рейтинг: Цена: 16096.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is the first to provide a comprehensive account of neural networks from a statistical perspective. Its emphasis is on pattern recognition, which currently represents the area of greatest applicability for neural networks. By focusing on pattern recognition, the book provides a much more extensive treatment of many topics than is available in earlier books.
Автор: Dancygier Название: The Cambridge Handbook of Cognitive Linguistics ISBN: 1107118441 ISBN-13(EAN): 9781107118447 Издательство: Cambridge Academ Рейтинг: Цена: 24394.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A comprehensive survey of the quickly developing discipline of cognitive linguistics, its rich methodology, key results, and interdisciplinary context. Providing an accessible overview of research questions, basic concepts, and various theoretical approaches, the Handbook places linguistic facts in the context of gesture studies, neuroscience, computational approaches, and many other fields.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
