Interpretable Artificial Intelligence: A Perspective of Granular Computing

Interpretable Artificial Intelligence: A Perspective of Granular Computing

Author: Witold Pedrycz

Publisher: Springer Nature

Published: 2021-03-26

Total Pages: 430

ISBN-13: 3030649490

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This book offers a comprehensive treatise on the recent pursuits of Artificial Intelligence (AI) – Explainable Artificial Intelligence (XAI) by casting the crucial features of interpretability and explainability in the original framework of Granular Computing. The innovative perspective established with the aid of information granules provides a high level of human centricity and transparency central to the development of AI constructs. The chapters reflect the breadth of the area and cover recent developments in the methodology, advanced algorithms and applications of XAI to visual analytics, knowledge representation, learning and interpretation. The book appeals to a broad audience including researchers and practitioners interested in gaining exposure to the rapidly growing body of knowledge in AI and intelligent systems.


Book Synopsis Interpretable Artificial Intelligence: A Perspective of Granular Computing by : Witold Pedrycz

Download or read book Interpretable Artificial Intelligence: A Perspective of Granular Computing written by Witold Pedrycz and published by Springer Nature. This book was released on 2021-03-26 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive treatise on the recent pursuits of Artificial Intelligence (AI) – Explainable Artificial Intelligence (XAI) by casting the crucial features of interpretability and explainability in the original framework of Granular Computing. The innovative perspective established with the aid of information granules provides a high level of human centricity and transparency central to the development of AI constructs. The chapters reflect the breadth of the area and cover recent developments in the methodology, advanced algorithms and applications of XAI to visual analytics, knowledge representation, learning and interpretation. The book appeals to a broad audience including researchers and practitioners interested in gaining exposure to the rapidly growing body of knowledge in AI and intelligent systems.


Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery

Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery

Author: Boris Kovalerchuk

Publisher: Springer Nature

Published:

Total Pages: 510

ISBN-13: 3031465490

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Book Synopsis Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery by : Boris Kovalerchuk

Download or read book Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery written by Boris Kovalerchuk and published by Springer Nature. This book was released on with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Applied Decision-Making

Applied Decision-Making

Author: Mauricio A. Sanchez

Publisher: Springer

Published: 2019-05-18

Total Pages: 215

ISBN-13: 3030179850

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This book gathers a collection of the latest research, applications, and proposals, introducing readers to innovations and concepts from diverse environments and systems. As such, it will provide students and professionals alike with not only cutting-edge information, but also new inspirations and potential research directions. Each chapter focuses on a specific aspect of applied decision making, e.g. in complex systems, computational intelligence, security, and ubiquitous computing.


Book Synopsis Applied Decision-Making by : Mauricio A. Sanchez

Download or read book Applied Decision-Making written by Mauricio A. Sanchez and published by Springer. This book was released on 2019-05-18 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers a collection of the latest research, applications, and proposals, introducing readers to innovations and concepts from diverse environments and systems. As such, it will provide students and professionals alike with not only cutting-edge information, but also new inspirations and potential research directions. Each chapter focuses on a specific aspect of applied decision making, e.g. in complex systems, computational intelligence, security, and ubiquitous computing.


Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery

Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery

Author: Boris Kovalerchuk

Publisher: Springer Nature

Published: 2022-06-04

Total Pages: 671

ISBN-13: 3030931196

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This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering "n-D glasses," where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain. This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level. The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations. The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.


Book Synopsis Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery by : Boris Kovalerchuk

Download or read book Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery written by Boris Kovalerchuk and published by Springer Nature. This book was released on 2022-06-04 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering "n-D glasses," where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain. This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level. The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations. The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.


Ethics of Artificial Intelligence

Ethics of Artificial Intelligence

Author: Francisco Lara

Publisher: Springer Nature

Published: 2024-01-01

Total Pages: 254

ISBN-13: 3031481356

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This book presents the reader with a comprehensive and structured understanding of the ethics of Artificial Intelligence (AI). It describes the main ethical questions that arise from the use of AI in different areas, as well as the contribution of various academic disciplines such as legal policy, environmental sciences, and philosophy of technology to the study of AI. AI has become ubiquitous and is significantly changing our lives, in many cases, for the better, but it comes with ethical challenges. These challenges include issues with the possibility and consequences of autonomous AI systems, privacy and data protection, the development of a surveillance society, problems with the design of these technologies and inequalities in access to AI technologies. This book offers specialists an instrument to develop a rigorous understanding of the main debates in emerging ethical questions around AI. The book will be of great relevance to experts in applied and technology ethics and to students pursuing degrees in applied ethics and, more specifically, in AI ethics.


Book Synopsis Ethics of Artificial Intelligence by : Francisco Lara

Download or read book Ethics of Artificial Intelligence written by Francisco Lara and published by Springer Nature. This book was released on 2024-01-01 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the reader with a comprehensive and structured understanding of the ethics of Artificial Intelligence (AI). It describes the main ethical questions that arise from the use of AI in different areas, as well as the contribution of various academic disciplines such as legal policy, environmental sciences, and philosophy of technology to the study of AI. AI has become ubiquitous and is significantly changing our lives, in many cases, for the better, but it comes with ethical challenges. These challenges include issues with the possibility and consequences of autonomous AI systems, privacy and data protection, the development of a surveillance society, problems with the design of these technologies and inequalities in access to AI technologies. This book offers specialists an instrument to develop a rigorous understanding of the main debates in emerging ethical questions around AI. The book will be of great relevance to experts in applied and technology ethics and to students pursuing degrees in applied ethics and, more specifically, in AI ethics.


Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems

Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems

Author: Witold Pedrycz

Publisher: Springer Nature

Published: 2023-07-15

Total Pages: 239

ISBN-13: 3031320956

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The book provides a timely coverage of the paradigm of knowledge distillation—an efficient way of model compression. Knowledge distillation is positioned in a general setting of transfer learning, which effectively learns a lightweight student model from a large teacher model. The book covers a variety of training schemes, teacher–student architectures, and distillation algorithms. The book covers a wealth of topics including recent developments in vision and language learning, relational architectures, multi-task learning, and representative applications to image processing, computer vision, edge intelligence, and autonomous systems. The book is of relevance to a broad audience including researchers and practitioners active in the area of machine learning and pursuing fundamental and applied research in the area of advanced learning paradigms.


Book Synopsis Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems by : Witold Pedrycz

Download or read book Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems written by Witold Pedrycz and published by Springer Nature. This book was released on 2023-07-15 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a timely coverage of the paradigm of knowledge distillation—an efficient way of model compression. Knowledge distillation is positioned in a general setting of transfer learning, which effectively learns a lightweight student model from a large teacher model. The book covers a variety of training schemes, teacher–student architectures, and distillation algorithms. The book covers a wealth of topics including recent developments in vision and language learning, relational architectures, multi-task learning, and representative applications to image processing, computer vision, edge intelligence, and autonomous systems. The book is of relevance to a broad audience including researchers and practitioners active in the area of machine learning and pursuing fundamental and applied research in the area of advanced learning paradigms.


Data Analysis and Optimization

Data Analysis and Optimization

Author: Boris Goldengorin

Publisher: Springer Nature

Published: 2023-09-23

Total Pages: 447

ISBN-13: 3031316541

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This book presents the state-of-the-art in the emerging field of data science and includes models for layered security with applications in the protection of sites—such as large gathering places—through high-stake decision-making tasks. Such tasks include cancer diagnostics, self-driving cars, and others where wrong decisions can possibly have catastrophic consequences. Additionally, this book provides readers with automated methods to analyze patterns and models for various types of data, with applications ranging from scientific discovery to business intelligence and analytics. The book primarily includes exploratory data analysis, pattern mining, clustering, and classification supported by real life case studies. The statistical section of this book explores the impact of data mining and modeling on the predictability assessment of time series. Further new notions of mean values based on ideas of multi-criteria optimization are compared with their conventional definitions, leading to new algorithmic approaches to the calculation of the suggested new means. The style of the written chapters and the provision of a broad yet in-depth overview of data mining, integrating novel concepts from machine learning and statistics, make the book accessible to upper level undergraduate and graduate students in data mining courses. Students and professionals specializing in computer and management science, data mining for high-dimensional data, complex graphs and networks will benefit from the cutting-edge ideas and practically motivated case studies in this book.


Book Synopsis Data Analysis and Optimization by : Boris Goldengorin

Download or read book Data Analysis and Optimization written by Boris Goldengorin and published by Springer Nature. This book was released on 2023-09-23 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state-of-the-art in the emerging field of data science and includes models for layered security with applications in the protection of sites—such as large gathering places—through high-stake decision-making tasks. Such tasks include cancer diagnostics, self-driving cars, and others where wrong decisions can possibly have catastrophic consequences. Additionally, this book provides readers with automated methods to analyze patterns and models for various types of data, with applications ranging from scientific discovery to business intelligence and analytics. The book primarily includes exploratory data analysis, pattern mining, clustering, and classification supported by real life case studies. The statistical section of this book explores the impact of data mining and modeling on the predictability assessment of time series. Further new notions of mean values based on ideas of multi-criteria optimization are compared with their conventional definitions, leading to new algorithmic approaches to the calculation of the suggested new means. The style of the written chapters and the provision of a broad yet in-depth overview of data mining, integrating novel concepts from machine learning and statistics, make the book accessible to upper level undergraduate and graduate students in data mining courses. Students and professionals specializing in computer and management science, data mining for high-dimensional data, complex graphs and networks will benefit from the cutting-edge ideas and practically motivated case studies in this book.


Explainable Machine Learning in Medicine

Explainable Machine Learning in Medicine

Author: Karol Przystalski

Publisher: Springer Nature

Published: 2023-12-28

Total Pages: 92

ISBN-13: 3031448774

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This book covers a variety of advanced communications technologies that can be used to analyze medical data and can be used to diagnose diseases in clinic centers. The book is a primer of methods for medicine, providing an overview of explainable artificial intelligence (AI) techniques that can be applied in different medical challenges. The authors discuss how to select and apply the proper technology depending on the provided data and the analysis desired. Because a variety of data can be used in the medical field, the book explains how to deal with challenges connected with each type. A number of scenarios are introduced that can happen in real-time environments, with each pared with a type of machine learning that can be used to solve it.


Book Synopsis Explainable Machine Learning in Medicine by : Karol Przystalski

Download or read book Explainable Machine Learning in Medicine written by Karol Przystalski and published by Springer Nature. This book was released on 2023-12-28 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a variety of advanced communications technologies that can be used to analyze medical data and can be used to diagnose diseases in clinic centers. The book is a primer of methods for medicine, providing an overview of explainable artificial intelligence (AI) techniques that can be applied in different medical challenges. The authors discuss how to select and apply the proper technology depending on the provided data and the analysis desired. Because a variety of data can be used in the medical field, the book explains how to deal with challenges connected with each type. A number of scenarios are introduced that can happen in real-time environments, with each pared with a type of machine learning that can be used to solve it.


Intelligent Information Systems

Intelligent Information Systems

Author: Jochen De Weerdt

Publisher: Springer Nature

Published: 2022-05-27

Total Pages: 148

ISBN-13: 3031074815

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This book constitutes the thoroughly refereed proceedings of the CAiSE Forum 2022 which was held in Leuven, Belgium, in June 2022, as part of the 34th International Conference on Advanced Information Systems Engineering, CAiSE 2022. The CAiSE Forum is a place within the CAiSE conference for presenting and discussing new ideas and tools related to information systems engineering. Intended to serve as an interactive platform, the Forum aims at the presentation of emerging new topics and controversial positions, as well as demonstration of innovative systems, tools and applications. The 15 full papers presented in this volume were carefully reviewed and selected from 24 submissions.


Book Synopsis Intelligent Information Systems by : Jochen De Weerdt

Download or read book Intelligent Information Systems written by Jochen De Weerdt and published by Springer Nature. This book was released on 2022-05-27 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the CAiSE Forum 2022 which was held in Leuven, Belgium, in June 2022, as part of the 34th International Conference on Advanced Information Systems Engineering, CAiSE 2022. The CAiSE Forum is a place within the CAiSE conference for presenting and discussing new ideas and tools related to information systems engineering. Intended to serve as an interactive platform, the Forum aims at the presentation of emerging new topics and controversial positions, as well as demonstration of innovative systems, tools and applications. The 15 full papers presented in this volume were carefully reviewed and selected from 24 submissions.


Integrated Uncertainty in Knowledge Modelling and Decision Making

Integrated Uncertainty in Knowledge Modelling and Decision Making

Author: Katsuhiro Honda

Publisher: Springer Nature

Published: 2023-10-26

Total Pages: 388

ISBN-13: 3031467817

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These two volumes constitute the proceedings of the 10th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2023, held in Kanazawa, Japan, during November 2-4, 2023. The 58 full papers presented were carefully reviewed and selected from 107 submissions. The papers deal with all aspects of research results, ideas, and experiences of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.


Book Synopsis Integrated Uncertainty in Knowledge Modelling and Decision Making by : Katsuhiro Honda

Download or read book Integrated Uncertainty in Knowledge Modelling and Decision Making written by Katsuhiro Honda and published by Springer Nature. This book was released on 2023-10-26 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: These two volumes constitute the proceedings of the 10th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2023, held in Kanazawa, Japan, during November 2-4, 2023. The 58 full papers presented were carefully reviewed and selected from 107 submissions. The papers deal with all aspects of research results, ideas, and experiences of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.