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Cybersecurity for Artificial Intelligence, Stamp


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Цена: 20962.00р.
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Автор: Stamp
Название:  Cybersecurity for Artificial Intelligence
ISBN: 9783030970864
Издательство: Springer
Классификация:

ISBN-10: 3030970868
Обложка/Формат: Hardback
Страницы: 380
Вес: 0.76 кг.
Дата издания: 30.07.2022
Серия: Advances in Information Security
Язык: English
Издание: 1st ed. 2022
Иллюстрации: 150 tables, color; 155 illustrations, color; 29 illustrations, black and white; xvi, 380 p. 184 illus., 155 illus. in color.
Размер: 235 x 155
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity. The provided research goes beyond simply applying AI techniques to datasets and instead delves into deeper issues that arise at the interface between deep learning and cybersecurity. This book also provides insight into the difficult how and why questions that arise in AI within the security domain. For example, this book includes chapters covering explainable AI, adversarial learning, resilient AI, and a wide variety of related topics. It’s not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Researchers and advanced level students working and studying in the fields of cybersecurity (equivalently, information security) or artificial intelligence (including deep learning, machine learning, big data, and related fields) will want to purchase this book as a reference. Practitioners working within these fields will also be interested in purchasing this book.
Дополнительное описание: Part I: Malware-Related Topics.- Generation of Adversarial Malware and Benign Examples using Reinforcement Learning.- Auxiliary-Classifier GAN for Malware Analysis.- Assessing the Robustness of an Image-based Malware Classifier with Small Level Perturbati



Computational Intelligence for Machine Learning and Healthcare Informatics

Автор: Rajshree Srivastava, Pradeep Kumar Mallick, Siddha
Название: Computational Intelligence for Machine Learning and Healthcare Informatics
ISBN: 3110647826 ISBN-13(EAN): 9783110647822
Издательство: Walter de Gruyter
Цена: 20446.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS
By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.

Robotics Through Science Fiction: Artificial Intelligence Explained Through Six Classic Robot Short Stories

Автор: Murphy Robin R.
Название: Robotics Through Science Fiction: Artificial Intelligence Explained Through Six Classic Robot Short Stories
ISBN: 0262536269 ISBN-13(EAN): 9780262536264
Издательство: MIT Press
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Цена: 2772.00 р.
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Описание:

Six classic science fiction stories and commentary that illustrate and explain key algorithms or principles of artificial intelligence.

This book presents six classic science fiction stories and commentary that illustrate and explain key algorithms or principles of artificial intelligence. Even though all the stories were originally published before 1973, they help readers grapple with two questions that stir debate even today: how are intelligent robots programmed? and what are the limits of autonomous robots? The stories--by Isaac Asimov, Vernor Vinge, Brian Aldiss, and Philip K. Dick--cover telepresence, behavior-based robotics, deliberation, testing, human-robot interaction, the "uncanny valley," natural language understanding, machine learning, and ethics. Each story is preceded by an introductory note, "As You Read the Story," and followed by a discussion of its implications, "After You Have Read the Story." Together with the commentary, the stories offer a nontechnical introduction to robotics. The stories can also be considered as a set of--admittedly fanciful--case studies to be read in conjunction with more serious study.

Contents
"Stranger in Paradise" by Isaac Asimov, 1973
"Runaround" by Isaac Asimov, 1942
"Long Shot" by Vernor Vinge, 1972
"Catch That Rabbit" by Isaac Asimov, 1944
"Super-Toys Last All Summer Long" by Brian Aldiss, 1969
"Second Variety" by Philip K. Dick, 1953

The Promise of Artificial Intelligence: Reckoning and Judgment

Автор: Smith Brian Cantwell
Название: The Promise of Artificial Intelligence: Reckoning and Judgment
ISBN: 0262043041 ISBN-13(EAN): 9780262043045
Издательство: MIT Press
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Цена: 4224.00 р.
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Описание: An argument that--despite dramatic advances in the field--artificial intelligence is nowhere near developing systems that are genuinely intelligent.

In this provocative book, Brian Cantwell Smith argues that artificial intelligence is nowhere near developing systems that are genuinely intelligent. Second wave AI, machine learning, even visions of third-wave AI: none will lead to human-level intelligence and judgment, which have been honed over millennia. Recent advances in AI may be of epochal significance, but human intelligence is of a different order than even the most powerful calculative ability enabled by new computational capacities. Smith calls this AI ability "reckoning," and argues that it does not lead to full human judgment--dispassionate, deliberative thought grounded in ethical commitment and responsible action.

Taking judgment as the ultimate goal of intelligence, Smith examines the history of AI from its first-wave origins ("good old-fashioned AI," or GOFAI) to such celebrated second-wave approaches as machine learning, paying particular attention to recent advances that have led to excitement, anxiety, and debate. He considers each AI technology's underlying assumptions, the conceptions of intelligence targeted at each stage, and the successes achieved so far. Smith unpacks the notion of intelligence itself--what sort humans have, and what sort AI aims at.

Smith worries that, impressed by AI's reckoning prowess, we will shift our expectations of human intelligence. What we should do, he argues, is learn to use AI for the reckoning tasks at which it excels while we strengthen our commitment to judgment, ethics, and the world.

Machine Learning for Future Wireless Communications

Автор: Fa–Long Luo
Название: Machine Learning for Future Wireless Communications
ISBN: 1119562252 ISBN-13(EAN): 9781119562252
Издательство: Wiley
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Цена: 18683.00 р.
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Описание:

A comprehensive review to the theory, application and research of machine learning for future wireless communications

In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities.

Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author - a noted expert on the topic - covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource:

  • Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks
  • Covers a range of topics from architecture and optimization to adaptive resource allocations
  • Reviews state-of-the-art machine learning based solutions for network coverage
  • Includes an overview of the applications of machine learning algorithms in future wireless networks
  • Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing

Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

The Art of Feature Engineering: Essentials for Machine Learning

Автор: Pablo Duboue
Название: The Art of Feature Engineering: Essentials for Machine Learning
ISBN: 1108709389 ISBN-13(EAN): 9781108709385
Издательство: Cambridge Academ
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Цена: 6970.00 р.
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Описание: This is a guide for data scientists who want to use feature engineering to improve the performance of their machine learning solutions. The book provides a unified view of the field, beginning with basic concepts and techniques, followed by a cross-domain approach to advanced topics, like texts and images, with hands-on case studies.

Machine Learning And Artificial Intelligence In Geosciences,61

Автор: Moseley, Benjamin
Название: Machine Learning And Artificial Intelligence In Geosciences,61
ISBN: 0128216697 ISBN-13(EAN): 9780128216699
Издательство: Elsevier Science
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Цена: 27791.00 р.
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Описание: Advances in Geophysics, Volume 61 - Machine Learning and Artificial Intelligence in Geosciences the latest release in this highly-respected publication in the field of geophysics, contains new chapters on a variety of topics, including Marchenko imaging, Machine learning and inversion, A review of reduced-order modelling approaches based on machine-learning and graphs for simulation of flow and transport through fractured media, and more.

Malware Analysis Using Artificial Intelligence and Deep Learning

Автор: Stamp Mark, Alazab Mamoun, Shalaginov Andrii
Название: Malware Analysis Using Artificial Intelligence and Deep Learning
ISBN: 3030625818 ISBN-13(EAN): 9783030625818
Издательство: Springer
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Цена: 25155.00 р.
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Описание: This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis.

Machine Intelligence and Big Data Analytics for Cybersecurity Applications

Автор: Maleh Yassine, Shojafar Mohammad, Alazab Mamoun
Название: Machine Intelligence and Big Data Analytics for Cybersecurity Applications
ISBN: 3030570231 ISBN-13(EAN): 9783030570231
Издательство: Springer
Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis.

Machine Intelligence and Big Data Analytics for Cybersecurity Applications

Автор: Maleh Yassine, Shojafar Mohammad, Alazab Mamoun
Название: Machine Intelligence and Big Data Analytics for Cybersecurity Applications
ISBN: 3030570266 ISBN-13(EAN): 9783030570262
Издательство: Springer
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Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis.

Latest Advances in Inductive Logic Programming

Автор: Muggleton Stephen, Watanabe Hiroaki
Название: Latest Advances in Inductive Logic Programming
ISBN: 1783265086 ISBN-13(EAN): 9781783265084
Издательство: World Scientific Publishing
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Цена: 12830.00 р.
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Описание: This book represents a selection of papers presented at the Inductive Logic Programming (ILP) workshop held at Cumberland Lodge, Great Windsor Park.

Principles of Automated Negotiation

Автор: Fatima
Название: Principles of Automated Negotiation
ISBN: 1107002540 ISBN-13(EAN): 9781107002548
Издательство: Cambridge Academ
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Цена: 7602.00 р.
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Описание: With an increasing number of applications in the context of multi-agent systems, automated negotiation is a rapidly growing area. Written by top researchers in the field, this state-of-the-art treatment of the subject explores key issues involved in the design of negotiating agents, covering strategic, heuristic, and axiomatic approaches. The authors discuss the potential benefits of automated negotiation as well as the unique challenges it poses for computer scientists and for researchers in artificial intelligence. They also consider possible applications and give readers a feel for the types of domains where automated negotiation is already being deployed. This book is ideal for graduate students and researchers in computer science who are interested in multi-agent systems. It will also appeal to negotiation researchers from disciplines such as management and business studies, psychology and economics.

Cognitive Computing: Implementing Big Data Machine Learning Solutions

Автор: Hurwitz, Kaufman Marcia, Bowles Adrian
Название: Cognitive Computing: Implementing Big Data Machine Learning Solutions
ISBN: 1118896629 ISBN-13(EAN): 9781118896624
Издательство: Wiley
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Цена: 6018.00 р.
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Описание: A comprehensive guide to learning technologies that unlock the value in big data Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data.


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