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Supervised Learning with Quantum Computers, Maria Schuld; Francesco Petruccione


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Автор: Maria Schuld; Francesco Petruccione
Название:  Supervised Learning with Quantum Computers
ISBN: 9783030071882
Издательство: Springer
Классификация:





ISBN-10: 303007188X
Обложка/Формат: Soft cover
Страницы: 287
Вес: 0.47 кг.
Дата издания: 2018
Серия: Quantum Science and Technology
Язык: English
Издание: Softcover reprint of
Иллюстрации: 48 illustrations, color; 35 illustrations, black and white; xiii, 287 p. 83 illus., 48 illus. in color.
Размер: 234 x 156 x 16
Читательская аудитория: General (us: trade)
Основная тема: Physics
Ссылка на Издательство: Link
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Поставляется из: Германии
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.
Дополнительное описание: Introduction.- Background.- How quantum computers can classify data.- Organisation of the book.- Machine Learning.- Prediction.- Models.- Training.- Methods in machine learning.- Quantum Information.- Introduction to quantum theory.- Introduction to quan



Supervised learning with quantum computers

Автор: Schuld, Maria Petruccione, Francesco
Название: Supervised learning with quantum computers
ISBN: 3319964232 ISBN-13(EAN): 9783319964232
Издательство: Springer
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Цена: 25155.00 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.

Supervised and Unsupervised Learning for Data Science

Автор: Michael W. Berry; Azlinah Mohamed; Bee Wah Yap
Название: Supervised and Unsupervised Learning for Data Science
ISBN: 3030224740 ISBN-13(EAN): 9783030224745
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are included along with theoretical models of learning for a comprehensive reference to the field. The book is organized into eight chapters that cover the following topics: discretization, feature extraction and selection, classification, clustering, topic modeling, graph analysis and applications. Practitioners and graduate students can use the volume as an important reference for their current and future research and faculty will find the volume useful for assignments in presenting current approaches to unsupervised and semi-supervised learning in graduate-level seminar courses. The book is based on selected, expanded papers from the Fourth International Conference on Soft Computing in Data Science (2018).Includes new advances in clustering and classification using semi-supervised and unsupervised learning;Address new challenges arising in feature extraction and selection using semi-supervised and unsupervised learning;Features applications from healthcare, engineering, and text/social media mining that exploit techniques from semi-supervised and unsupervised learning.

Sampling Techniques for Supervised or Unsupervised Tasks

Автор: Fr?d?ric Ros; Serge Guillaume
Название: Sampling Techniques for Supervised or Unsupervised Tasks
ISBN: 3030293483 ISBN-13(EAN): 9783030293482
Издательство: Springer
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Цена: 16070.00 р.
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Описание: This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the “curse of dimensionality”, their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the ?eld and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementation and evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. 'This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge.'M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas

'In science the difficulty is not to have ideas, but it is to make them work'From Carlo Rovelli
Supervised Descriptive Pattern Mining

Автор: Sebasti?n Ventura; Jos? Mar?a Luna
Название: Supervised Descriptive Pattern Mining
ISBN: 3030074560 ISBN-13(EAN): 9783030074562
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book provides a general and comprehensible overview of supervised descriptive pattern mining, considering classic algorithms and those based on heuristics. It provides some formal definitions and a general idea about patterns, pattern mining, the usefulness of patterns in the knowledge discovery process, as well as a brief summary on the tasks related to supervised descriptive pattern mining. It also includes a detailed description on the tasks usually grouped under the term supervised descriptive pattern mining: subgroups discovery, contrast sets and emerging patterns. Additionally, this book includes two tasks, class association rules and exceptional models, that are also considered within this field.A major feature of this book is that it provides a general overview (formal definitions and algorithms) of all the tasks included under the term supervised descriptive pattern mining. It considers the analysis of different algorithms either based on heuristics or based on exhaustive search methodologies for any of these tasks. This book also illustrates how important these techniques are in different fields, a set of real-world applications are described.Last but not least, some related tasks are also considered and analyzed. The final aim of this book is to provide a general review of the supervised descriptive pattern mining field, describing its tasks, its algorithms, its applications, and related tasks (those that share some common features).This book targets developers, engineers and computer scientists aiming to apply classic and heuristic-based algorithms to solve different kinds of pattern mining problems and apply them to real issues. Students and researchers working in this field, can use this comprehensive book (which includes its methods and tools) as a secondary textbook.

Applications of Supervised and Unsupervised Ensemble Methods

Автор: Oleg Okun
Название: Applications of Supervised and Unsupervised Ensemble Methods
ISBN: 3642039987 ISBN-13(EAN): 9783642039980
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Expanding upon presentations at last year`s SUEMA (Supervised and Unsupervised Ensemble Methods and Applications) meeting, this volume explores recent developments in the field. Useful examples act as a guide for practitioners in computational intelligence.

Supervised Learning with Complex-valued Neural Networks

Автор: Sundaram Suresh; Narasimhan Sundararajan; Ramasamy
Название: Supervised Learning with Complex-valued Neural Networks
ISBN: 3642426794 ISBN-13(EAN): 9783642426797
Издательство: Springer
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Цена: 15672.00 р.
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Описание: A new generation of neural networks is needed in telecommunications, medical imaging and signal processing as signals become more complex and nonlinear. This survey of the latest complex-valued networks includes learning algorithms and new architectures.

Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning

Автор: Thorsten Wuest
Название: Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning
ISBN: 3319386980 ISBN-13(EAN): 9783319386980
Издательство: Springer
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Цена: 14365.00 р.
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Описание: The book reports on a novel approach for holistically identifying the relevant state drivers of complex, multi-stage manufacturing systems. In practice, this method can be used to identify the most important process parameters and state characteristics, the so-called state drivers, of a manufacturing system.

Quantum Information Theory

Автор: Wilde
Название: Quantum Information Theory
ISBN: 1107176166 ISBN-13(EAN): 9781107176164
Издательство: Cambridge Academ
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Цена: 10613.00 р.
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Описание: This new edition of Wilde`s popular book promises over 100 pages of new material, exercises and references. New attention is given to the derivation of the Choi-Kraus theorem for quantum channels, the CHSH game, quantum relative entropy, and sequential decoding. The text offers an ideal entry point into the topic for graduate students.

Principles Of Quantum Artificial Intelligence

Автор: Wichert Andreas
Название: Principles Of Quantum Artificial Intelligence
ISBN: 9814566748 ISBN-13(EAN): 9789814566742
Издательство: World Scientific Publishing
Цена: 12830.00 р.
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Описание: In this book, we introduce quantum computation and its application to AI. We highlight problem solving and knowledge representation framework. Based on information theory, we cover two main principles of quantum computation - Quantum Fourier transform and Grover search. Then, we indicate how these two principles can be applied to problem solving and finally present a general model of a quantum computer that is based on production systems.

Quantum Bio-Informatics V - Proceedings Of The Quantum Bio-Informatics 2011

Автор: Accardi Luigi Et Al
Название: Quantum Bio-Informatics V - Proceedings Of The Quantum Bio-Informatics 2011
ISBN: 981446001X ISBN-13(EAN): 9789814460019
Издательство: World Scientific Publishing
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Цена: 25344.00 р.
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Описание: This volume is based on the fifth international conference of quantum bio-informatics held at the QBI Center of Tokyo University of Science.This volume provides a platform to connect mathematics, physics, information and life sciences, and in particular, research for new paradigm for information science and life science on the basis of quantum theory.The following topics are discussed:

Quantum Information And Quantum Computing - Proceedings Of Symposium

Автор: Nakahara Mikio Et Al
Название: Quantum Information And Quantum Computing - Proceedings Of Symposium
ISBN: 9814425214 ISBN-13(EAN): 9789814425216
Издательство: World Scientific Publishing
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Цена: 14414.00 р.
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Описание: The open research center project "Interdisciplinary fundamental research toward realization of a quantum computer" has been supported by the Ministry of Education, Japan for five years. This book is a collection of the research outcomes by the members engaged in the project.

Interface Between Quantum Information And Statistical Physics

Автор: Nakahara Mikio Et Al
Название: Interface Between Quantum Information And Statistical Physics
ISBN: 9814425273 ISBN-13(EAN): 9789814425278
Издательство: World Scientific Publishing
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Цена: 15682.00 р.
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Описание: This book is a collection of contributions to the Symposium on Interface between Quantum Information and Statistical Physics held at Kinki University in November 2011. Subjects of the symposium include quantum adiabatic computing, quantum simulator using bosons, classical statistical physics, among others. Contributions to this book are prepared in a self-contained manner so that a reader with a modest background may understand the subjects.


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