Concise Guide To Quantum Machine Learning
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Concise Guide To Quantum Machine Learning
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Author : Davide Pastorello
language : en
Publisher:
Release Date : 2023
Concise Guide To Quantum Machine Learning written by Davide Pastorello and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Artificial intelligence. Robotics. Simulation. Graphics categories.
This book offers a brief but effective introduction to quantum machine learning (QML). QML is not merely a translation of classical machine learning techniques into the language of quantum computing, but rather a new approach to data representation and processing. Accordingly, the content is not divided into a "classical part" that describes standard machine learning schemes and a "quantum part" that addresses their quantum counterparts. Instead, to immerse the reader in the quantum realm from the outset, the book starts from fundamental notions of quantum mechanics and quantum computing. Avoiding unnecessary details, it presents the concepts and mathematical tools that are essential for the required quantum formalism. In turn, it reviews those quantum algorithms most relevant to machine learning. Later chapters highlight the latest advances in this field and discuss the most promising directions for future research. To gain the most from this book, a basic grasp of statistics and linear algebra is sufficient; no previous experience with quantum computing or machine learning is needed. The book is aimed at researchers and students with no background in quantum physics and is also suitable for physicists looking to enter the field of QML.
Concise Guide To Quantum Machine Learning
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Author : Davide Pastorello
language : en
Publisher: Springer Nature
Release Date : 2022-12-16
Concise Guide To Quantum Machine Learning written by Davide Pastorello and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-16 with Computers categories.
This book offers a brief but effective introduction to quantum machine learning (QML). QML is not merely a translation of classical machine learning techniques into the language of quantum computing, but rather a new approach to data representation and processing. Accordingly, the content is not divided into a “classical part” that describes standard machine learning schemes and a “quantum part” that addresses their quantum counterparts. Instead, to immerse the reader in the quantum realm from the outset, the book starts from fundamental notions of quantum mechanics and quantum computing. Avoiding unnecessary details, it presents the concepts and mathematical tools that are essential for the required quantum formalism. In turn, it reviews those quantum algorithms most relevant to machine learning. Later chapters highlight the latest advances in this field and discuss the most promising directions for future research. To gain the most from this book, a basic grasp of statistics and linear algebra is sufficient; no previous experience with quantum computing or machine learning is needed. The book is aimed at researchers and students with no background in quantum physics and is also suitable for physicists looking to enter the field of QML.
Computer Safety Reliability And Security Safecomp 2024 Workshops
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Author : Andrea Ceccarelli
language : en
Publisher: Springer Nature
Release Date : 2024-09-08
Computer Safety Reliability And Security Safecomp 2024 Workshops written by Andrea Ceccarelli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-08 with Computers categories.
This book constitutes the proceedings of the Workshops held in conjunction with the 43rd International Conference on Computer Safety, Reliability, and Security, SAFECOMP 2024, which took place in Florence, Italy, during September 2024. The 36 papers included in this book were carefully reviewed and selected from a total of 64 submissions to the following workshops: DECSoS 2024 – 19th Workshop on Dependable Smart Embedded and Cyber-Physical Systems and Systems-of-Systems SASSUR 2024 - 11th International Workshop on Next Generation of System Assurance Approaches for Critical Systems TOASTS 2024 – Towards A Safer Systems’ Architecture Through Security WAISE 2024 – 7th International Workshop on Artificial Intelligence Safety Engineering
Game Theory A Concise Guide
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Author : Nova Martian
language : en
Publisher: Walzone Press
Release Date : 2025-01-24
Game Theory A Concise Guide written by Nova Martian and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-24 with Mathematics categories.
"Game Theory: A Concise Guide" offers an engaging exploration into the fundamental principles and applications of game theory, making this intricate field accessible to a broad audience. Crafted with clarity and precision, the book presents essential concepts such as Nash Equilibrium, dominant strategies, and the dynamics of cooperative versus non-cooperative games. Each chapter delves into these core topics, blending theoretical underpinnings with practical examples to illustrate the profound impact of strategic decision-making across various disciplines. With a focus on real-world applications, this guide examines how game theory informs business strategies, economic modeling, and political decision-making. It demonstrates its relevance from corporate boardrooms to international diplomacy, illustrating how strategic interactions shape outcomes in complex settings. Additionally, the book addresses the current challenges and limitations of game theory, offering a balanced perspective that encourages critical reflection on its applicability. Whether for students, professionals, or curious readers, "Game Theory: A Concise Guide" serves as both an introduction and a thoughtful review of this pivotal analytical tool.
Concise Guide To Computation Theory
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Author : Akira Maruoka
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-29
Concise Guide To Computation Theory written by Akira Maruoka and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-29 with Computers categories.
This textbook presents a thorough foundation to the theory of computation. Combining intuitive descriptions and illustrations with rigorous arguments and detailed proofs for key topics, the logically structured discussion guides the reader through the core concepts of automata and languages, computability, and complexity of computation. Topics and features: presents a detailed introduction to the theory of computation, complete with concise explanations of the mathematical prerequisites; provides end-of-chapter problems with solutions, in addition to chapter-opening summaries and numerous examples and definitions throughout the text; draws upon the author’s extensive teaching experience and broad research interests; discusses finite automata, context-free languages, and pushdown automata; examines the concept, universality and limitations of the Turing machine; investigates computational complexity based on Turing machines and Boolean circuits, as well as the notion of NP-completeness.
Reservoir Computing
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Author : Kohei Nakajima
language : en
Publisher: Springer Nature
Release Date : 2021-08-05
Reservoir Computing written by Kohei Nakajima and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-05 with Computers categories.
This book is the first comprehensive book about reservoir computing (RC). RC is a powerful and broadly applicable computational framework based on recurrent neural networks. Its advantages lie in small training data set requirements, fast training, inherent memory and high flexibility for various hardware implementations. It originated from computational neuroscience and machine learning but has, in recent years, spread dramatically, and has been introduced into a wide variety of fields, including complex systems science, physics, material science, biological science, quantum machine learning, optical communication systems, and robotics. Reviewing the current state of the art and providing a concise guide to the field, this book introduces readers to its basic concepts, theory, techniques, physical implementations and applications. The book is sub-structured into two major parts: theory and physical implementations. Both parts consist of a compilation of chapters, authored by leading experts in their respective fields. The first part is devoted to theoretical developments of RC, extending the framework from the conventional recurrent neural network context to a more general dynamical systems context. With this broadened perspective, RC is not restricted to the area of machine learning but is being connected to a much wider class of systems. The second part of the book focuses on the utilization of physical dynamical systems as reservoirs, a framework referred to as physical reservoir computing. A variety of physical systems and substrates have already been suggested and used for the implementation of reservoir computing. Among these physical systems which cover a wide range of spatial and temporal scales, are mechanical and optical systems, nanomaterials, spintronics, and quantum many body systems. This book offers a valuable resource for researchers (Ph.D. students and experts alike) and practitioners working in the field of machine learning, artificial intelligence, robotics, neuromorphic computing, complex systems, and physics.
A Practical Guide To Quantum Machine Learning And Quantum Optimization
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Author : Elias F. Combarro
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-03-31
A Practical Guide To Quantum Machine Learning And Quantum Optimization written by Elias F. Combarro and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-31 with Computers categories.
Work with fully explained algorithms and ready-to-use examples that can be run on quantum simulators and actual quantum computers with this comprehensive guide Key FeaturesGet a solid grasp of the principles behind quantum algorithms and optimization with minimal mathematical prerequisitesLearn the process of implementing the algorithms on simulators and actual quantum computersSolve real-world problems using practical examples of methodsBook Description This book provides deep coverage of modern quantum algorithms that can be used to solve real-world problems. You'll be introduced to quantum computing using a hands-on approach with minimal prerequisites. You'll discover many algorithms, tools, and methods to model optimization problems with the QUBO and Ising formalisms, and you will find out how to solve optimization problems with quantum annealing, QAOA, Grover Adaptive Search (GAS), and VQE. This book also shows you how to train quantum machine learning models, such as quantum support vector machines, quantum neural networks, and quantum generative adversarial networks. The book takes a straightforward path to help you learn about quantum algorithms, illustrating them with code that's ready to be run on quantum simulators and actual quantum computers. You'll also learn how to utilize programming frameworks such as IBM's Qiskit, Xanadu's PennyLane, and D-Wave's Leap. Through reading this book, you will not only build a solid foundation of the fundamentals of quantum computing, but you will also become familiar with a wide variety of modern quantum algorithms. Moreover, this book will give you the programming skills that will enable you to start applying quantum methods to solve practical problems right away. What you will learnReview the basics of quantum computingGain a solid understanding of modern quantum algorithmsUnderstand how to formulate optimization problems with QUBOSolve optimization problems with quantum annealing, QAOA, GAS, and VQEFind out how to create quantum machine learning modelsExplore how quantum support vector machines and quantum neural networks work using Qiskit and PennyLaneDiscover how to implement hybrid architectures using Qiskit and PennyLane and its PyTorch interfaceWho this book is for This book is for professionals from a wide variety of backgrounds, including computer scientists and programmers, engineers, physicists, chemists, and mathematicians. Basic knowledge of linear algebra and some programming skills (for instance, in Python) are assumed, although all mathematical prerequisites will be covered in the appendices.
Quantum Machine Learning With Python
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Author : Santanu Pattanayak
language : en
Publisher: Apress
Release Date : 2021-03-29
Quantum Machine Learning With Python written by Santanu Pattanayak and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-29 with Computers categories.
Quickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use cases that can be solved through Quantum based algorithms.This book explains Quantum Computing, which leverages the Quantum mechanical properties sub-atomic particles. It also examines Quantum machine learning, which can help solve some of the most challenging problems in forecasting, financial modeling, genomics, cybersecurity, supply chain logistics, cryptography among others. You'll start by reviewing the fundamental concepts of Quantum Computing, such as Dirac Notations, Qubits, and Bell state, followed by postulates and mathematical foundations of Quantum Computing. Once the foundation base is set, you'll delve deep into Quantum based algorithms including Quantum Fourier transform, phase estimation, and HHL (Harrow-Hassidim-Lloyd) among others. You'll then be introduced to Quantum machine learning and Quantum deep learning-based algorithms, along with advanced topics of Quantum adiabatic processes and Quantum based optimization. Throughout the book, there are Python implementations of different Quantum machine learning and Quantum computing algorithms using the Qiskit toolkit from IBM and Cirq from Google Research. What You'll Learn Understand Quantum computing and Quantum machine learning Explore varied domains and the scenarios where Quantum machine learning solutions can be applied Develop expertise in algorithm development in varied Quantum computing frameworks Review the major challenges of building large scale Quantum computers and applying its various techniques Who This Book Is For Machine Learning enthusiasts and engineers who want to quickly scale up to Quantum Machine Learning
Hands On Quantum Machine Learning With Python
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Author : Frank Zickert
language : en
Publisher: Independently Published
Release Date : 2021-06-19
Hands On Quantum Machine Learning With Python written by Frank Zickert and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-19 with categories.
You're interested in quantum computing and machine learning. But you don't know how to get started? Let me help! Whether you just get started with quantum computing and machine learning or you're already a senior machine learning engineer, Hands-On Quantum Machine Learning With Python is your comprehensive guide to get started with Quantum Machine Learning - the use of quantum computing for the computation of machine learning algorithms. Quantum computing promises to solve problems intractable with current computing technologies. But is it fundamentally different and asks us to change the way we think. Hands-On Quantum Machine Learning With Python strives to be the perfect balance between theory taught in a textbook and the actual hands-on knowledge you'll need to implement real-world solutions. Inside this book, you will learn the basics of quantum computing and machine learning in a practical and applied manner.
Quantum Security
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Author : Christopher Murphy
language : en
Publisher: Springer Nature
Release Date : 2025-02-24
Quantum Security written by Christopher Murphy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-24 with Computers categories.
In a world where cybersecurity threats evolve daily, it’s time to leave traditional, flawed security models behind. This book introduces a groundbreaking approach that applies the quantum principle of superposition to user authentication. Just as a particle exists in multiple states until observed, a user’s presence on a network remains undefined until their Digital ID is verified. Once verified, their identity collapses into a single truth—eliminating any risk of impersonation or fraud. This book demonstrates how Digital IDs transform the very foundation of network security. Unlike conventional methods, where user identity is indirectly represented through data, this model ties a user’s existence directly to their Digital ID. By securing user presence—and absence—this new authentication model offers unparalleled protection from unauthorized access and common cyber threats like stolen credentials or malicious impersonation. It equips cybersecurity professionals, C-suite executives, and decision-makers with practical, actionable steps for seamlessly integrating this new technology into existing infrastructures. Readers will explore how Digital IDs create a secure, private interface when connected to the network, and how they prevent unauthorized actions when the user is absent. This innovative shift moves security from reactive mitigation strategies to proactive solutions that ensure both trust and control. What You Will Learn: The difference between indirect and direct authentication and how the current cybersecurity approach is fundamentally flawed. Practical steps for implementing digital IDs and direct user interaction to eliminate common cyber threats. How to shift from reactive mitigation strategies to proactive, long-term security solutions that significantly reduce vulnerabilities. Straightforward, actionable insights on how to transform current cybersecurity infrastructures for more robust protection. Who This Book is for: This book is written primarily for cybersecurity professionals such as CISOs, CTOs, CIOs, network architects, and IT security managers. These readers have a deep understanding of current cybersecurity challenges but are seeking innovative, more effective solutions to overcome systemic flaws in today’s network security models. Secondary audiences include business leaders and decision-makers in organizations, who need to understand the strategic importance of cybersecurity innovations like Digital IDs and Direct User Interaction. Tertiary audiences might include students or researchers in cybersecurity who want to explore alternative security models.