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This book provides students, researchers and practitioners with a deep understanding of the theory of online auctions and gives practical examples of how to implement in modern-day internet systems.

Privacy and Consumer Empowerment in Online Advertising provides an overview of the different issues that are in play in consumer privacy and in empowering consumers with rights to manage the privacy of their data. The authors review the existing knowledge on this topic and discuss implications for consumers, for advertisers, and for ad serving platforms that enable advertisers to reach consumers.The introductory section provides an outline and briefly reviews the key ideas. Section 2 discusses the key aspects of the GDPR, the CCPA and the CPRA. Since the implementation of the GDPR in May 2018, some early empirical evidence has emerged of its impact and this is examined in Section 3. The authors review the privacy and economic frameworks in Section 4. Section 5 discusses the theoretical work in this area enhances our understanding of the impact of privacy regulation on consumers and on online advertising. Section 6 examines how consumers are presented with privacy notices and their (in)ability to make privacy choices due to a variety of factors. Section 7 reviews how firms attach value to consumers' data. In light of the passing of privacy regulation, firms have been attempting to develop methods for privacy-preserving targeted advertising. In Section 8, we discuss some of these attempts such as FLoC and TURTLEDOVE, which aim to target consumers based on their interests and/or their website visit history, but without compromising their privacy. Finally, Section 9 concludes with a discussion.An overall summary is that privacy concerns have been heightened in the past two decades and this has led to the passing of privacy regulations addressing data security and privacy rights. After these regulations, a significant minority of consumers have chosen to not provide consent for their data to be collected, used and shared. However, most consumers still do not properly understand the key implications of privacy policies of firms, and more efforts are needed in that regard. Also, technologies are being developed for privacy-preserving user targeting. Finally, regarding firms, data frictions caused by privacy regulations have, in turn, caused negative consequences for small advertisers, publishers and service providers. The authors provide some directions for future work that may be valuable to move thinking forward on this increasingly important topic.

The comprehensive review of neurosymbolic programming introduces the reader to the topic and provides an insightful treatise on an increasingly important topic at the intersection of programming languages and machine learning.

This book is an introduction to Acceleration Methods used in convex optimization that enables the reader to quickly understand the important principles and apply the techniques to their own research.

This monograph reviews the work that HCI and other disciplines has produced on the digital transcendent experience and combines it with an illustrated design fiction.

Presents some existing and new results on analysis and design of finite-time and fixed-time converging systems. Two main groups of approaches for analysis/synthesis of this kind of convergence, Lyapunov functions and the theory of homogeneous systems, are considered.

Reviews research on the design and evaluation of search user interfaces of the past 10 years. It integrates state-of-the-art research in the areas of information seeking behavior, information retrieval, and human-computer interaction on the topic of search interface.

This monograph focusses on the current research activities and emerging trends that relate to numerous technological functionalities, and it should be of interest to students, researchers and engineers active in the fields related to Circuits and Systems for Biomedical Engineering.

Variational autoencoders (VAEs) are powerful deep generative models widely used to represent high-dimensional complex data through a low-dimensional latent space learned in an unsupervised manner. In this volume, the authors introduce and discuss a general class of models, called dynamical variational autoencoders.

The book is a self-contained treatment of a topic that sits at the intersection of machine learning and formal verification. It can serve as an introduction to the field for first-year graduate students or senior undergraduates, even if they have not been exposed to deep learning or verification.

This book provides an accessible overview of the complexities of generalized coordination for students, researchers and practitioners alike. Covering both theory and practical issues, the authors provide examples throughout to clearly illustrate the concepts being discussed.

Presents the findings and recommendations of a study conducted by the Hellenic Institute of Advanced Study. By presenting various applications and possibilities, this monograph should appeal to persons involved specifically with robotics, and technology development in general.

Working at the intersection of information theory and neighboring disciplines, the authors provide a comprehensive survey of a particular area of asymptotic frame theory that can drastically improve the performance of codes used in communication and signal processing systems.

Written in a tutorial style, readers from both classical and quantum backgrounds will find this an enlightening treatise on the topic. This monograph is a comprehensive and accessible overview of a complex problem for students and researchers in signal processing.

Beyond ESG: Reforming Capitalism and Social Democracy analyzes various reform projects, discusses the concepts of ethics and equity and proposes projects for in-depth reforms of capitalism and social democracy.

Accounting for Risk is about using accounting information to assess risk and the required return for bearing that risk. The focus is on investing in firms and the equity claims on firms: How much should an investor discount the price of a share in a firm for risk, and how can accounting information help to answer that question?

The Economics of Securities Regulation: A Survey gives an overview of the U.S. regulatory system, explores the justifications for regulating securities markets, and describes the qualitative and quantitative literature that assesses the regulatory system's effectiveness.

This publication presents state-of-the-art designs of the most critical building blocks of the analog/digital interface highlighting new and innovative circuit architectures and techniques.

Analyses the most recent literature on IPOs of entrepreneurial firms - young firms based on intangible rather than physical assets where the founder of the firm often serves as the key inventor and the CEO.

Reflects the respect, affection and high esteem that his colleagues held for Mike Wright. This volume presents a collection of reflections paying tribute to him, as a scholar, as an academic leader and scholarly innovator, and as a special person.

Inspired by the nanopass framework for teaching compilation, this book shows how to implement refinement types via a progression of languages that incrementally add features to the language or type system. The book provides an insightful introduction into Refinement Types using an innovative tutorial style that enables fast learning.

Tensor Regression is the first thorough overview of the fundamentals, motivations, popular algorithms, strategies for efficient implementation, related applications, available datasets, and software resources for tensor-based regression analysis.

This monograph provides a comprehensive overview of the role of institutional investors in corporate governance.

Provides an overview of Efficiency and Productivity Analysis, a very important field of research and practice, spanning over and engaging with many disciplines, most prominently Economics (theoretical and applied), Statistics (and therefore Econometrics), Operations Research and Management Science.

Minimum-Distortion Embedding describes the theory behind and practical use of a cutting-edge artificial intelligence technique. Accompanied by an open-source software package, PyMDE, it illustrates applying these AI techniques in areas such as images, co- networks, demographics, genetics, and biology.