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Bayesian Optimization
A comprehensive introduction to Bayesian optimization that starts from scratch and carefully develops all the key ideas along the way.
Artificial Intelligence and Machine Learning
This book is designed for undergraduates, postgraduates and professionals who want to have a firm grip on the fundamental principles of AI and ML. Artificial Intelligence (AI) is a broad area of knowledge which has percolated into every aspect of human life. ‘Machine Learning algorithms’ are considered to be a subset of AI Theory, mathematics and coding are three aspects to any topic in AI. This book covers the most relevant topics in the field of Artificial Intelligence and Machine Learning (ML). The subdivisions of Machine Learning are Supervised, Unsupervised and Reinforcement learning. All three are covered in sufficient depth. One very important and upcoming field of application is ...
Ultra-Reliable and Low-Latency Communications (URLLC) Theory and Practice
Ultra-Reliable and Low-Latency Communications (URLLC) Theory and Practice Comprehensive resource presenting important recent advances in wireless communications for URLLC services, including device-to-device communication, multi-connectivity, and more Ultra-Reliable and Low-Latency Communications (URLLC) Theory and Practice discusses the typical scenarios, possible solutions, and state-of-the-art techniques that enable URLLC in different perspectives from the physical layer to higher-level approaches, aiming to tackle URLLC’s challenges with both theoretical and practical approaches, which bridges the lacuna between theory and practice. With long-term contributions to the development of fu...
Alternative Assets and Cryptocurrencies
Alternative assets such as fine art, wine, or diamonds have become popular investment vehicles in the aftermath of the global financial crisis. Correlation with classical financial markets is typically low, such that diversification benefits arise for portfolio allocation and risk management. Cryptocurrencies share many alternative asset features, but are hampered by high volatility, sluggish commercial acceptance, and regulatory uncertainties. This collection of papers addresses alternative assets and cryptocurrencies from economic, financial, statistical, and technical points of view. It gives an overview of their current state and explores their properties and prospects using innovative approaches and methodologies.
Visual Rhetoric and the Eloquence of Design
The essays in VISUAL RHETORIC AND THE ELOQUENCE OF DESIGN foreground the rhetorical functions of design artifacts. Rhetoric, normally understood as verbal or visual messages that have a tactical persuasive objective—a speech that wants to convince us to vote for someone, or an ad that tries to persuade us to buy a particular product—becomes in Visual Rhetoric and the Eloquence of Design the persuasive use of a broad set of meta-beliefs. Designed objects are particularly effective at this second level of persuasion because they offer audiences communicative data that reflect, and also orchestrate, a potentially broad array of cultural concerns. Persuasion entails both the aesthetic form and material composition of any object.
Reinforcement Learning
Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This exciting development avoids constraints found in traditional machine learning (ML) algorithms. This practical book shows data science and AI professionals how to learn by reinforcement and enable a machine to learn by itself. Author Phil Winder of Winder Research covers everything from basic building blocks to state-of-the-art practices. You'll explore the current state of RL, focus on industrial applications, learn numerous algorithms, and benefit from dedicated chapters on deploying RL solutions to product...
Foundations of Semantic Communication Networks
Comprehensive overview of the principles, theories, and techniques needed to build end-to-end semantic communication systems, with case studies included. In this rapidly evolving landscape, the integration of connected intelligence applications highlights the pressing need for networks to gain intelligence in a non-siloed and ad hoc manner. The traditional incremental approach to network design is no longer sufficient to support the diverse and dynamic requirements of these emerging applications. This necessitates a paradigm shift towards more intelligent and adaptive network architectures. From theory to application, Foundations of Semantic Communication Networks describes and provides a co...
Distributional Reinforcement Learning
The first comprehensive guide to distributional reinforcement learning, providing a new mathematical formalism for thinking about decisions from a probabilistic perspective. Distributional reinforcement learning is a new mathematical formalism for thinking about decisions. Going beyond the common approach to reinforcement learning and expected values, it focuses on the total reward or return obtained as a consequence of an agent's choices—specifically, how this return behaves from a probabilistic perspective. In this first comprehensive guide to distributional reinforcement learning, Marc G. Bellemare, Will Dabney, and Mark Rowland, who spearheaded development of the field, present its key...
Automated Machine Learning and Meta-Learning for Multimedia
This book disseminates and promotes the recent research progress and frontier development on AutoML and meta-learning as well as their applications on computer vision, natural language processing, multimedia and data mining related fields. These are exciting and fast-growing research directions in the general field of machine learning. The authors advocate novel, high-quality research findings, and innovative solutions to the challenging problems in AutoML and meta-learning. This topic is at the core of the scope of artificial intelligence, and is attractive to audience from both academia and industry. This book is highly accessible to the whole machine learning community, including: researchers, students and practitioners who are interested in AutoML, meta-learning, and their applications in multimedia, computer vision, natural language processing and data mining related tasks. The book is self-contained and designed for introductory and intermediate audiences. No special prerequisite knowledge is required to read this book.
