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ENGLISH

Ai-Driven Mechanism Design

by Pingzhong Tang, Song Zuo e Weiran Shen

~~237,84€~~ 214,06€ 10% OFF

 For example, it can reduce the mechanism space significantly, build more realistic buyer models, and better balance different objectives.The book focuses on several aspects of mechanism design and demonstrates that the framework is useful in both theoretical analysis and practical applications.
ENGLISH

Machine Learning Safety

by Gaojie Jin, Wenjie Ruan e Xiaowei Huang

~~67,58€~~ 60,82€ 10% OFF

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 Machine learning algorithms allow computers to learn without being explicitly programmed. and adversarial training, which is used to enhance the training process and reduce vulnerabilities. The book aims to improve readersâ€™ awareness of the potential safety issues regarding machine learning models.
ENGLISH

Hypergraph Computation

by Qionghai Dai e Yue Gao

47,30€ + 10% CARD

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 The content of this book consists of hypergraph computation paradigms, hypergraph modelling, hypergraph structure evolution, hypergraph neural networks, and applications of hypergraph computation in different fields.
ENGLISH

Neural Text-To-Speech Synthesis

by Xu Tan

172,24€ + 10% CARD

 <p>Text-to-speech (TTS) aims to synthesize intelligible and natural speech based on the given text. It is a hot topic in language, speech, and machine learning research and has broad applications in industry. This book introduces neural network-based TTS in the era of deep learning, aiming to provide a good understanding of neural TTS, current research and applications, and the future research trend.</p><p>This book first introduces the history of TTS technologies and overviews neural TTS, and provides preliminary knowledge on language and speech processing, neural networks and deep learning, and deep generative models. It then introduces neural TTS from the perspective of key components (text analyses, acoustic models, vocoders, and end-to-end models) and advanced topics (expressive and controllable, robust, model-efficient, and data-efficient TTS). It also points some future research directions and collects some resources related to TTS.</p><p>This book is the first to introduceneural TTS in a comprehensive and easy-to-understand way and can serve both academic researchers and industry practitioners working on TTS.</p><br><p></p>
ENGLISH

Machine Learning Safety

by Gaojie Jin, Wenjie Ruan e Xiaowei Huang

66,24€ + 10% CARD

 Machine learning algorithms allow computers to learn without being explicitly programmed. and adversarial training, which is used to enhance the training process and reduce vulnerabilities. The book aims to improve readersâ€™ awareness of the potential safety issues regarding machine learning models.
ENGLISH

Ai Ethics - A Textbook

by Paula Boddington

59,61€ + 10% CARD

 <p>This book introduces readers to critical ethical concerns in the development and use of artificial intelligence. Offering clear and accessible information on central concepts and debates in AI ethics, it explores how related problems are now forcing us to address fundamental, age-old questions about human life, value, and meaning. In addition, the book shows how foundational and theoretical issues relate to concrete controversies, with an emphasis on understanding how ethical questions play out in practice.</p><p>All topics are explored in depth, with clear explanations of relevant debates in ethics and philosophy, drawing on both historical and current sources. Questions in AI ethics are explored in the context of related issues in technology, regulation, society, religion, and culture, to help readers gain a nuanced understanding of the scope of AI ethics within broader debates and concerns.</p>Written with both students and educators in mind, the book is easy to use, with keyterms clearly explained, and numerous exercises designed to stretch and challenge. It offers readers essential insights into the evolving field of AI ethics. Moreover, it presents a range of methods and strategies that can be used to analyse and understand ethical questions, which are illustrated throughout with case studies. <p></p><br>
ENGLISH

Heterogeneous Graph Representation Learning And Applications

by Chuan Shi, Philip S. Yu e Xiao Wang

184,84€ + 10% CARD

 Representation learning in heterogeneous graphs (HG) is intended to provide a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized recommendation, node classification, etc. This task, however, is challenging not only because of the need to incorporate heterogeneous structural (graph) information consisting of multiple types of node and edge, but also the need to consider heterogeneous attributes or types of content (e.g. text or image) associated with each node. Although considerable advances have been made in homogeneous (and heterogeneous) graph embedding, attributed graph embedding and graph neural networks, few are capable of simultaneously and effectively taking into account heterogeneous structural (graph) information as well as the heterogeneous content information of each node.<div><br></div><div>In this book, we provide a comprehensive survey of current developments in HG representation learning.More importantly, we present the state-of-the-art in this field, including theoretical models and real applications that have been showcased at the top conferences and journals, such as TKDE, KDD, WWW, IJCAI and AAAI. The book has two major objectives: (1) to provide researchers with an understanding of the fundamental issues and a good point of departure for working in this rapidly expanding field, and (2) to present the latest research on applying heterogeneous graphs to model real systems and learning structural features of interaction systems. To the best of our knowledge, it is the first book to summarize the latest developments and present cutting-edge research on heterogeneous graph representation learning. To gain the most from it, readers should have a basic grasp of computer science, data mining and machine learning.<div> <div> <div> <p><br></p></div> </div> </div></div>
ENGLISH

Towards A Code Of Ethics For Artificial Intelligence

by Paula Boddington

72,86€ + 10% CARD

 <p>The author investigates how to produce realistic and workable ethical codes or regulations in this rapidly developing field to address the immediate and realistic longer-term issues facing us. She spells out the key ethical debates concisely, exposing all sides of the arguments, and addresses how codes of ethics or other regulations might feasibly be developed, looking for pitfalls and opportunities, drawing on lessons learned in other fields, and explaining key points of professional ethics.</p><p>The book provides a useful resource for those aiming to address the ethical challenges of AI research in meaningful and practical ways. </p>
ENGLISH

Feature Selection For High-Dimensional Data

by Amparo Alonso-Betanzos, Noelia Sanchez-Marono e Veronica Bolon-Canedo

59,61€ + 10% CARD

 <p>This book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems, explaining the foundations, real application problems and the challenges of feature selection for high-dimensional data.</p><p>The authors first focus on the analysis and synthesis of feature selection algorithms, presenting a comprehensive review of basic concepts and experimental results of the most well-known algorithms. </p><p>They then address different real scenarios with high-dimensional data, showing the use of feature selection algorithms in different contexts with different requirements and information: microarray data, intrusion detection, tear film lipid layer classification and cost-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces, such as scalability, distributed processing and real-time processing, scenarios that open up new and interesting challenges for researchers.</p><p>The book is useful for practitioners, researchers and graduate students in the areas of machine learning and data mining.</p>
ENGLISH

Non-Prioritized Belief Change

by Eduardo Ferme, Marco Garapa e Mauricio D. L. Reis

~~189,25€~~ 170,33€ 10% OFF

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ENGLISH

Ai Ethics - A Textbook

by Paula Boddington

81,10€

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ENGLISH

Machine Learning Safety

by Gaojie Jin, Wenjie Ruan e Xiaowei Huang

87,86€

free shipping

OUT OF STOCK OR NOT AVAILABLE

 Machine learning algorithms allow computers to learn without being explicitly programmed. and adversarial training, which is used to enhance the training process and reduce vulnerabilities. The book aims to improve readersâ€™ awareness of the potential safety issues regarding machine learning models.
Electronic Institutions - Applications To Uhelp, Wecurate And Peerlearn

82,73€

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OUT OF STOCK OR NOT AVAILABLE

 This book introduces the concept of Electronic Institutions (EIs), where complex interactions between human or software agents are governed by specified rules, mirroring those found in human organisations.

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