Statistical Analysis Techniques in Particle Physics - Fits, Density Estimation and Supervised Learning, Narsky
Автор: Hvitfeldt Emil, Silge Julia Название: Supervised Machine Learning for Text Analysis in R ISBN: 0367554186 ISBN-13(EAN): 9780367554187 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is designed to provide practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate text into their modeling pipelines. We assume that the reader is somewhat familiar with R, predictive modeling concepts for non-text data, and the tidyverse family of packages.
Автор: Hvitfeldt Emil, Silge Julia Название: Supervised Machine Learning for Text Analysis in R ISBN: 0367554194 ISBN-13(EAN): 9780367554194 Издательство: Taylor&Francis Рейтинг: Цена: 7961.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is designed to provide practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate text into their modeling pipelines. We assume that the reader is somewhat familiar with R, predictive modeling concepts for non-text data, and the tidyverse family of packages.
Автор: Maria Schuld; Francesco Petruccione Название: Supervised Learning with Quantum Computers ISBN: 303007188X ISBN-13(EAN): 9783030071882 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.
Автор: Silverman, Bernard. W. Название: Density Estimation for Statistics and Data Analysis ISBN: 0412246201 ISBN-13(EAN): 9780412246203 Издательство: Taylor&Francis Рейтинг: Цена: 20671.00 р. Наличие на складе: Нет в наличии.
Автор: Scott David W. Название: Multivariate Density Estimation ISBN: 0471697559 ISBN-13(EAN): 9780471697558 Издательство: Wiley Рейтинг: Цена: 15198.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written to convey an intuitive feeling for both theory and practice, this book illustrates what a powerful tool density estimation can be when used not only with univariate and bivariate data but also in the higher dimensions of trivariate and quadrivariate information.
Автор: Scrucca, Luca Fraley, Chris Murphy, T. Brendan Adrian E., Raftery Название: Model-based clustering, classification, and density estimation using mclust in r ISBN: 1032234954 ISBN-13(EAN): 9781032234953 Издательство: Taylor&Francis Рейтинг: Цена: 8114.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing methods to be understood within the context of statistical modeling.
Автор: P.P.B. Eggermont; V.N. LaRiccia Название: Maximum Penalized Likelihood Estimation ISBN: 0387952683 ISBN-13(EAN): 9780387952680 Издательство: Springer Рейтинг: Цена: 25853.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Deals with parametric and nonparametric density estimation from the maximum (penalized) likelihood point of view, including estimation under constraints such as unimodality and log-concavity. This book focuses on convexity and convex optimization, as applied to maximum penalized likelihood estimation.
Описание: This book describes computational problems related to kernel density estimation (KDE)-one of the most important and widely used data smoothing techniques. This book is an attempt to remedy this. The book primarily addresses researchers and advanced graduate or postgraduate students who are interested in KDE and its computational aspects.
Название: Combinatorial Methods in Density Estimation ISBN: 1461265274 ISBN-13(EAN): 9781461265276 Издательство: Springer Рейтинг: Цена: 14673.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Density estimation has evolved enormously since the days of bar plots and histograms, but researchers and users are still struggling with the problem of the selection of the bin widths.
Автор: P.P.B. Eggermont; V.N. LaRiccia Название: Maximum Penalized Likelihood Estimation ISBN: 1441929282 ISBN-13(EAN): 9781441929280 Издательство: Springer Рейтинг: Цена: 25853.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book deals with parametric and nonparametric density estimation from the maximum (penalized) likelihood point of view, including estimation under constraints.
Описание: This thesis presents analytical theoretical studies on the interplay between charge density waves (CDW) and superconductivity (SC) in the actively studied transition-metal dichalcogenide 1T-TiSe2. It begins by reapproaching a years-long debate over the nature of the phase transition to the commensurate CDW (CCDW) state and the role played by the intrinsic tendency towards excitonic condensation in this system. A Ginzburg-Landau phenomenological theory was subsequently developed to understand the experimentally observed transition from commensurate to incommensurate CDW (ICDW) order with doping or pressure, and the emergence of a superconducting dome that coexists with ICDW. Finally, to characterize microscopically the effects of the interplay between CDW and SC, the spectrum of CDW fluctuations beyond mean-field was studied in detail. In the aggregate, the work reported here provides an encompassing understanding of what are possibly key microscopic underpinnings of the CDW and SC physics in TiSe2.
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