Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download Accountable And Explainable Methods For Complex Reasoning Over Text full books in PDF, epub, and Kindle. Read online Accountable And Explainable Methods For Complex Reasoning Over Text ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author : Pepa Atanasova
Publisher : Springer Nature
ISBN 13 : 3031515188
Total Pages : 208 pages
Book Rating : 4.0/5 (315 download)
Download or read book Accountable and Explainable Methods for Complex Reasoning over Text written by Pepa Atanasova and published by Springer Nature. This book was released on with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Wojciech Samek
Publisher : Springer Nature
ISBN 13 : 3030289540
Total Pages : 435 pages
Book Rating : 4.0/5 (32 download)
Download or read book Explainable AI: Interpreting, Explaining and Visualizing Deep Learning written by Wojciech Samek and published by Springer Nature. This book was released on 2019-09-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Author : Mohammad Amir Khusru Akhtar
Publisher : Springer Nature
ISBN 13 : 3031664892
Total Pages : 381 pages
Book Rating : 4.0/5 (316 download)
Download or read book Towards Ethical and Socially Responsible Explainable AI written by Mohammad Amir Khusru Akhtar and published by Springer Nature. This book was released on with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Christoph Molnar
Publisher : Lulu.com
ISBN 13 : 0244768528
Total Pages : 320 pages
Book Rating : 4.2/5 (447 download)
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Author : Luca Longo
Publisher : Springer Nature
ISBN 13 : 303163800X
Total Pages : 471 pages
Book Rating : 4.0/5 (316 download)
Download or read book Explainable Artificial Intelligence written by Luca Longo and published by Springer Nature. This book was released on with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Joachim Diederich
Publisher : Springer
ISBN 13 : 3540753907
Total Pages : 267 pages
Book Rating : 4.5/5 (47 download)
Download or read book Rule Extraction from Support Vector Machines written by Joachim Diederich and published by Springer. This book was released on 2007-12-27 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Support vector machines (SVMs) are one of the most active research areas in machine learning. SVMs have shown good performance in a number of applications, including text and image classification. However, the learning capability of SVMs comes at a cost – an inherent inability to explain in a comprehensible form, the process by which a learning result was reached. Hence, the situation is similar to neural networks, where the apparent lack of an explanation capability has led to various approaches aiming at extracting symbolic rules from neural networks. For SVMs to gain a wider degree of acceptance in fields such as medical diagnosis and security sensitive areas, it is desirable to offer an explanation capability. User explanation is often a legal requirement, because it is necessary to explain how a decision was reached or why it was made. This book provides an overview of the field and introduces a number of different approaches to extracting rules from support vector machines developed by key researchers. In addition, successful applications are outlined and future research opportunities are discussed. The book is an important reference for researchers and graduate students, and since it provides an introduction to the topic, it will be important in the classroom as well. Because of the significance of both SVMs and user explanation, the book is of relevance to data mining practitioners and data analysts.
Author : Kamal Malik
Publisher : CRC Press
ISBN 13 : 1040099297
Total Pages : 205 pages
Book Rating : 4.0/5 (4 download)
Download or read book Explainable Artificial Intelligence for Autonomous Vehicles written by Kamal Malik and published by CRC Press. This book was released on 2024-08-14 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explainable AI for Autonomous Vehicles: Concepts, Challenges, and Applications is a comprehensive guide to developing and applying explainable artificial intelligence (XAI) in the context of autonomous vehicles. It begins with an introduction to XAI and its importance in developing autonomous vehicles. It also provides an overview of the challenges and limitations of traditional black-box AI models and how XAI can help address these challenges by providing transparency and interpretability in the decision-making process of autonomous vehicles. The book then covers the state-of-the-art techniques and methods for XAI in autonomous vehicles, including model-agnostic approaches, post-hoc explanations, and local and global interpretability techniques. It also discusses the challenges and applications of XAI in autonomous vehicles, such as enhancing safety and reliability, improving user trust and acceptance, and enhancing overall system performance. Ethical and social considerations are also addressed in the book, such as the impact of XAI on user privacy and autonomy and the potential for bias and discrimination in XAI-based systems. Furthermore, the book provides insights into future directions and emerging trends in XAI for autonomous vehicles, such as integrating XAI with other advanced technologies like machine learning and blockchain and the potential for XAI to enable new applications and services in the autonomous vehicle industry. Overall, the book aims to provide a comprehensive understanding of XAI and its applications in autonomous vehicles to help readers develop effective XAI solutions that can enhance autonomous vehicle systems' safety, reliability, and performance while improving user trust and acceptance. This book: Discusses authentication mechanisms for camera access, encryption protocols for data protection, and access control measures for camera systems. Showcases challenges such as integration with existing systems, privacy, and security concerns while implementing explainable artificial intelligence in autonomous vehicles. Covers explainable artificial intelligence for resource management, optimization, adaptive control, and decision-making. Explains important topics such as vehicle-to-vehicle (V2V) communication, vehicle-to-infrastructure (V2I) communication, remote monitoring, and control. Emphasizes enhancing safety, reliability, overall system performance, and improving user trust in autonomous vehicles. The book is intended to provide researchers, engineers, and practitioners with a comprehensive understanding of XAI's key concepts, challenges, and applications in the context of autonomous vehicles. It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, information technology, and automotive engineering.
Author : Robert Johnson
Publisher : HiTeX Press
ISBN 13 :
Total Pages : 206 pages
Book Rating : 4.:/5 (661 download)
Download or read book Introduction to Explainable AI (XAI) written by Robert Johnson and published by HiTeX Press. This book was released on 2024-10-27 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Introduction to Explainable AI (XAI): Making AI Understandable" is an essential resource for anyone seeking to understand the burgeoning field of explainable artificial intelligence. As AI systems become integral to critical decision-making processes across industries, the ability to interpret and comprehend their outputs becomes increasingly vital. This book offers a comprehensive exploration of XAI, delving into its foundational concepts, diverse techniques, and pivotal applications. It strives to demystify complex AI behaviors, ensuring that stakeholders across sectors can engage with AI technologies confidently and responsibly. Structured to cater to both beginners and those with an existing interest in AI, this book covers the spectrum of XAI topics, from model-specific approaches and interpretable machine learning to the ethical and societal implications of AI transparency. Readers will be equipped with practical insights into the tools and frameworks available for developing explainable models, alongside an understanding of the challenges and limitations inherent in the field. As we look toward the future, the book also addresses emerging trends and research directions, positioning itself as a definitive guide to navigating the evolving landscape of XAI. This book stands as an invaluable reference for students, practitioners, and policy makers alike, offering a balanced blend of theory and practical guidance. By focusing on the synergy between humans and machines through explainability, it underscores the importance of building AI systems that are not only powerful but also trustworthy and aligned with societal values.
Author : Przemyslaw Biecek
Publisher : CRC Press
ISBN 13 : 0429651376
Total Pages : 312 pages
Book Rating : 4.4/5 (296 download)
Download or read book Explanatory Model Analysis written by Przemyslaw Biecek and published by CRC Press. This book was released on 2021-02-15 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explanatory Model Analysis Explore, Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment. Today, the true bottleneck in predictive modelling is neither the lack of data, nor the lack of computational power, nor inadequate algorithms, nor the lack of flexible models. It is the lack of tools for model exploration (extraction of relationships learned by the model), model explanation (understanding the key factors influencing model decisions) and model examination (identification of model weaknesses and evaluation of model's performance). This book presents a collection of model agnostic methods that may be used for any black-box model together with real-world applications to classification and regression problems.
Author : Virginia Dignum
Publisher : Springer Nature
ISBN 13 : 3030303713
Total Pages : 133 pages
Book Rating : 4.0/5 (33 download)
Download or read book Responsible Artificial Intelligence written by Virginia Dignum and published by Springer Nature. This book was released on 2019-11-04 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens.
Author : B. K. Tripathy
Publisher : CRC Press
ISBN 13 : 1040099939
Total Pages : 355 pages
Book Rating : 4.0/5 (4 download)
Download or read book Explainable, Interpretable, and Transparent AI Systems written by B. K. Tripathy and published by CRC Press. This book was released on 2024-08-23 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transparent Artificial Intelligence (AI) systems facilitate understanding of the decision-making process and provide opportunities in various aspects of explaining AI models. This book provides up-to-date information on the latest advancements in the field of explainable AI, which is a critical requirement of AI, Machine Learning (ML), and Deep Learning (DL) models. It provides examples, case studies, latest techniques, and applications from domains such as healthcare, finance, and network security. It also covers open-source interpretable tool kits so that practitioners can use them in their domains. Features: Presents a clear focus on the application of explainable AI systems while tackling important issues of “interpretability” and “transparency”. Reviews adept handling with respect to existing software and evaluation issues of interpretability. Provides insights into simple interpretable models such as decision trees, decision rules, and linear regression. Focuses on interpreting black box models like feature importance and accumulated local effects. Discusses capabilities of explainability and interpretability. This book is aimed at graduate students and professionals in computer engineering and networking communications.
Author : Lakshmi D
Publisher : CRC Press
ISBN 13 : 1040038832
Total Pages : 335 pages
Book Rating : 4.0/5 (4 download)
Download or read book Explainable AI (XAI) for Sustainable Development written by Lakshmi D and published by CRC Press. This book was released on 2024-06-26 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain. • Focuses on virtual machine placement and migration techniques for cloud data centres • Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services • Includes application of placement techniques for quality of service, performance, and reliability improvement • Explores data centre resource management, load balancing and orchestration using machine learning techniques • Analyses dynamic and scalable resource scheduling with a focus on resource management The reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.
Author : Shahram Latifi
Publisher : Springer Nature
ISBN 13 : 3031283325
Total Pages : 428 pages
Book Rating : 4.0/5 (312 download)
Download or read book ITNG 2023 20th International Conference on Information Technology-New Generations written by Shahram Latifi and published by Springer Nature. This book was released on 2023-05-06 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume represents the 20th International Conference on Information Technology - New Generations (ITNG), 2023. ITNG is an annual event focusing on state of the art technologies pertaining to digital information and communications. The applications of advanced information technology to such domains as astronomy, biology, education, geosciences, security, and health care are the among topics of relevance to ITNG. Visionary ideas, theoretical and experimental results, as well as prototypes, designs, and tools that help the information readily flow to the user are of special interest. Machine Learning, Robotics, High Performance Computing, and Innovative Methods of Computing are examples of related topics. The conference features keynote speakers, a best student award, poster award, service award, a technical open panel, and workshops/exhibits from industry, government and academia. This publication is unique as it captures modern trends in IT with a balance of theoretical and experimental work. Most other work focus either on theoretical or experimental, but not both. Accordingly, we do not know of any competitive literature.
Author : Hans de Bruijn
Publisher : Routledge
ISBN 13 : 1134042248
Total Pages : 174 pages
Book Rating : 4.1/5 (34 download)
Download or read book Management in Networks written by Hans de Bruijn and published by Routledge. This book was released on 2012-08-21 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Getting what you want – even if you are the boss – isn’t always easy. Almost every organization, big or small, works among a network of competing interests. Whether it's governments pushing through policies, companies trying to increase profits, or even families deciding where to move house, rarely can decisions be made in isolation from competing interests both within the organization and outside it. In this accessible and straightforward account, Hans de Bruijn and Ernst ten Heuvelhof cast light on multi-stakeholder decision-making. Shunning simplistic model talk, they reveal the nuts and bolts of decision-making within the numerous dilemmas and tensions at work. Using a diverse range of illustrative examples throughout, their perceptive analysis examines how different interests can either support or block change, and the strategies available in managing a variety of stakeholders This insightful text provides both depth of understanding and a wealth of advice. It is invaluable reading to students working in business and management, public administration and organizational studies, plus practitioners – or actors – operating in a range of contexts.
Author : Shaliesh S
Publisher : Co-Text Publishers
ISBN 13 : 8195791751
Total Pages : 86 pages
Book Rating : 4.1/5 (957 download)
Download or read book ADVANCES IN EMERGING COMPUTING TECHNOLOGIES written by Shaliesh S and published by Co-Text Publishers. This book was released on 2023-08-19 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: PUBLISHED BY CO-TEXT PUBLISHERS IN ASSOCIATION WITH DEPARTMENT OF COMPUTER SCIENCE SACRED HEART COLLEGE (AUTONOMOUS) THEVARA, KOCHI-682013, KERALA, INDIA
Author : Hugo Jair Escalante
Publisher : Springer
ISBN 13 : 3319981315
Total Pages : 305 pages
Book Rating : 4.3/5 (199 download)
Download or read book Explainable and Interpretable Models in Computer Vision and Machine Learning written by Hugo Jair Escalante and published by Springer. This book was released on 2018-11-29 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning. Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: · Evaluation and Generalization in Interpretable Machine Learning · Explanation Methods in Deep Learning · Learning Functional Causal Models with Generative Neural Networks · Learning Interpreatable Rules for Multi-Label Classification · Structuring Neural Networks for More Explainable Predictions · Generating Post Hoc Rationales of Deep Visual Classification Decisions · Ensembling Visual Explanations · Explainable Deep Driving by Visualizing Causal Attention · Interdisciplinary Perspective on Algorithmic Job Candidate Search · Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions · Inherent Explainability Pattern Theory-based Video Event Interpretations
Author : Surbhi Bhatia Khan
Publisher : Elsevier
ISBN 13 : 0323999492
Total Pages : 342 pages
Book Rating : 4.3/5 (239 download)
Download or read book Innovations in Artificial Intelligence and Human-Computer Interaction in the Digital Era written by Surbhi Bhatia Khan and published by Elsevier. This book was released on 2023-07-22 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era investigates the interaction and growing interdependency of the HCI and AI fields, which are not usually addressed in traditional approaches. Chapters explore how well AI can interact with users based on linguistics and user-centered design processes, especially with the advances of AI and the hype around many applications. Other sections investigate how HCI and AI can mutually benefit from a closer association and the how the AI community can improve their usage of HCI methods like "Wizard of Oz prototyping and "Thinking aloud protocols. Moreover, HCI can further augment human capabilities using new technologies. This book demonstrates how an interdisciplinary team of HCI and AI researchers can develop extraordinary applications, such as improved education systems, smart homes, smart healthcare and map Human Computer Interaction (HCI) for a multidisciplinary field that focuses on the design of computer technology and the interaction between users and computers in different domains. - Presents fundamental concepts of both HCI and AI, addressing a multidisciplinary audience of researchers and engineers working on User Centered Design (UCD), User Interface (UI) design, and User Experience (UX) design - Explores a broad range of case studies from across healthcare, industry, and education - Investigates multiple strategies for designing and developing intelligent user interfaces to solve real-world problems - Outlines research challenges and future directions for the intersection of AI and HCI
