Evaluating Architectural Safeguards for Uncertain AI Black-Box Components

Evaluating Architectural Safeguards for Uncertain AI Black-Box Components
Author :
Publisher : KIT Scientific Publishing
Total Pages : 472
Release :
ISBN-10 : 9783731513209
ISBN-13 : 373151320X
Rating : 4/5 (20X Downloads)

Book Synopsis Evaluating Architectural Safeguards for Uncertain AI Black-Box Components by : Scheerer, Max

Download or read book Evaluating Architectural Safeguards for Uncertain AI Black-Box Components written by Scheerer, Max and published by KIT Scientific Publishing. This book was released on 2023-10-23 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability.


Evaluating Architectural Safeguards for Uncertain AI Black-Box Components Related Books

Evaluating Architectural Safeguards for Uncertain AI Black-Box Components
Language: en
Pages: 472
Authors: Scheerer, Max
Categories:
Type: BOOK - Published: 2023-10-23 - Publisher: KIT Scientific Publishing

GET EBOOK

Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more co
Context-based Access Control and Attack Modelling and Analysis
Language: en
Pages: 350
Authors: Walter, Maximilian
Categories:
Type: BOOK - Published: 2024-07-03 - Publisher: KIT Scientific Publishing

GET EBOOK

This work introduces architectural security analyses for detecting access violations and attack paths in software architectures. It integrates access control po
A Reference Structure for Modular Model-based Analyses
Language: en
Pages: 398
Authors: Koch, Sandro Giovanni
Categories:
Type: BOOK - Published: 2024-04-25 - Publisher: KIT Scientific Publishing

GET EBOOK

In this work, the authors analysed the co-dependency between models and analyses, particularly the structure and interdependence of artefacts and the feature-ba
Interpretable Machine Learning
Language: en
Pages: 320
Authors: Christoph Molnar
Categories: Computers
Type: BOOK - Published: 2020 - Publisher: Lulu.com

GET EBOOK

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simp
Regulating Artificial Intelligence
Language: en
Pages: 391
Authors: Thomas Wischmeyer
Categories: Law
Type: BOOK - Published: 2019-11-29 - Publisher: Springer Nature

GET EBOOK

This book assesses the normative and practical challenges for artificial intelligence (AI) regulation, offers comprehensive information on the laws that current