Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Learning and Reasoning in Hybrid Structured Spaces
Artificial intelligence often has to deal with uncertain scenarios, such as a partially observed environment or noisy observations. Traditional probabilistic models, while being very principled approaches in these contexts, are incapable of dealing with both algebraic and logical constraints. Existing hybrid continuous/discrete models are typically limited in expressivity, or do not offer any guarantee on the approximation errors. This book, Learning and Reasoning in Hybrid Structured Spaces, discusses a recent and general formalism called Weighted Model Integration (WMI), which enables probabilistic modeling and inference in hybrid structured domains. WMI-based inference algorithms differ w...
Advanced Tools and Methods for Treewidth-Based Problem Solving
This book, Advanced Tools and Methods for Treewidth-Based Problem Solving, contains selected results from the author’s PhD studies, which were carried out from 2015 to 2021. For his PhD thesis, Markus Hecher received the EurAI Dissertation Award 2021 and the GI Dissertation Award 2021, amongst others. The aim of the book is to present a new toolkit for using the structural parameter of treewidth to solve problems in knowledge representation and reasoning (KR) and artificial intelligence (AI), thereby establishing both theoretical upper and lower bounds, as well as methods to deal with treewidth efficiently in practice. The key foundations outlined in the book provide runtime lower bounds â...
Artificial Intelligence Research and Development
Artificial intelligence has become an integral part of all our lives. Development is rapid in this exciting and far-reaching field, and keeping up to date with the latest research and innovation is crucial to all those working with the technology. This book presents the proceedings of the 24th edition of CCIA, the International Conference of the Catalan Association for Artificial Intelligence, held in Sitges, Spain, from 19 – 21 October 2022. This annual event serves as a meeting point not only for researchers in AI from the Catalan speaking territories (southern France, Catalonia, Valencia, the Balearic Islands and Alghero in Italy) but for researchers from around the world. The programme...
Deep Learning with Relational Logic Representations
Deep learning has been used with great success in a number of diverse applications, ranging from image processing to game playing, and the fast progress of this learning paradigm has even been seen as paving the way towards general artificial intelligence. However, the current deep learning models are still principally limited in many ways. This book, ‘Deep Learning with Relational Logic Representations’, addresses the limited expressiveness of the common tensor-based learning representation used in standard deep learning, by generalizing it to relational representations based in mathematical logic. This is the natural formalism for the relational data omnipresent in the interlinked stru...
Computational and Methodological Statistics and Biostatistics
In the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes. Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and ...
Exploiting Environment Configurability in Reinforcement Learning
In recent decades, Reinforcement Learning (RL) has emerged as an effective approach to address complex control tasks. In a Markov Decision Process (MDP), the framework typically used, the environment is assumed to be a fixed entity that cannot be altered externally. There are, however, several real-world scenarios in which the environment can be modified to a limited extent. This book, Exploiting Environment Configurability in Reinforcement Learning, aims to formalize and study diverse aspects of environment configuration. In a traditional MDP, the agent perceives the state of the environment and performs actions. As a consequence, the environment transitions to a new state and generates a r...
Computational Models of Argument
Argumentation has traditionally been studied across a number of fields, notably philosophy, cognitive science, linguistics and jurisprudence. The study of computational models of argumentation is a more recent endeavor, bringing together researchers from traditional fields and computer science and engineering within a rich, interdisciplinary matrix. Computational models of argumentation have been identified and used since the 1980s, and more recently an important role for argumentation in leading to principled decisions has emerged in several settings. This book presents the proceedings of COMMA 2022 the 9th International Conference on Computational Models of Argument, held in Cardiff, Wales...
Image and Signal Processing for Networked eHealth Applications
E-health is closely related with networks and telecommunications when dealing with applications of collecting or transferring medical data from distant locations for performing remote medical collaborations and diagnosis. In this book we provide an overview of the fields of image and signal processing for networked and distributed e-health applications and their supporting technologies. The book is structured in 10 chapters, starting the discussion from the lower end, that of acquisition and processing of biosignals and medical images and ending in complex virtual reality systems and techniques providing more intuitive interaction in a networked medical environment. The book also discusses networked clinical decision support systems and corresponding medical standards, WWW-based applications, medical collaborative platforms, wireless networking, and the concepts of ambient intelligence and pervasive computing in electronic healthcare systems.
Decoupling
A friendly and systematic introduction to the theory and applications. The book begins with the sums of independent random variables and vectors, with maximal inequalities and sharp estimates on moments, which are later used to develop and interpret decoupling inequalities. Decoupling is first introduced as it applies to randomly stopped processes and unbiased estimation. The authors then proceed with the theory of decoupling in full generality, paying special attention to comparison and interplay between martingale and decoupling theory, and to applications. These include limit theorems, moment and exponential inequalities for martingales and more general dependence structures, biostatistical implications, and moment convergence in Anscombe's theorem and Wald's equation for U--statistics. Addressed to researchers in probability and statistics and to graduates, the expositon is at the level of a second graduate probability course, with a good portion of the material fit for use in a first year course.
Developing Students’ Statistical Reasoning
Increased attention is being paid to the need for statistically educated citizens: statistics is now included in the K-12 mathematics curriculum, increasing numbers of students are taking courses in high school, and introductory statistics courses are required in college. However, increasing the amount of instruction is not sufficient to prepare statistically literate citizens. A major change is needed in how statistics is taught. To bring about this change, three dimensions of teacher knowledge need to be addressed: their knowledge of statistical content, their pedagogical knowledge, and their statistical-pedagogical knowledge, i.e., their specific knowledge about how to teach statistics. T...
