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The Handbook of Computational Neurodegeneration provides a comprehensive overview of the field and thus bridges the gap between standard textbooks of research on neurodegeneration and dispersed publications for specialists that have a narrowed focus on computational methods to study this complicated process. The handbook reviews the central issues and methodological approaches related to the field for which the reader pursues a thorough overview. It also conveys more advanced knowledge, thus serving both as an introductory text and as a starting point for an in-depth study of a specific area, as well as a quick reference source for the expert by reflecting the state of the art and future prospects. The book includes topics that are usually missing in standard textbooks and that are only marginally represented in the specific literature. The broad scope of this handbook is reflected by five major parts that facilitate an integration of computational concepts, methods and applications in the study of neurodegeneration. Each part is intended to stand on its own, giving an overview of the topic and the most important problems and approaches, which are supported by examples, practical applications, and proposed methodologies. The basic concepts and knowledge, standard procedures and methods are presented, as well as recent advances and new perspectives. .

Neurosciences. --- Bioinformatics. --- Health informatics. --- Neural networks (Computer science) . --- Computational Biology/Bioinformatics. --- Health Informatics. --- Mathematical Models of Cognitive Processes and Neural Networks.

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This proceedings presents the result of the 8th International Conference in Network Analysis, held at the Higher School of Economics, Moscow, in May 2018. The conference brought together scientists, engineers, and researchers from academia, industry, and government. Contributions in this book focus on the development of network algorithms for data mining and its applications. Researchers and students in mathematics, economics, statistics, computer science, and engineering find this collection a valuable resource filled with the latest research in network analysis. Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks. Machine learning techniques in network settings including community detection, clustering, and biclustering algorithms are presented with applications to social network analysis.

Mathematical optimization. --- Neural networks (Computer science) . --- Combinatorics. --- Optimization. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Network analysis (Planning) --- Project networks --- Planning --- System analysis --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- Combinatorics --- Algebra --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing

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From artificial neural net / game theory / semantic applications, to modeling tools, smart manufacturing systems, and data science research – this book offers a broad overview of modern intelligent methods and applications of machine learning, evolutionary computation, Industry 4.0 technologies, and autonomous agents leading to the Internet of Things and potentially a new technological revolution. Though chiefly intended for IT professionals, it will also help a broad range of users of future emerging technologies adapt to the new smart / intelligent wave. In separate chapters, the book highlights fourteen successful examples of recent advances in the rapidly evolving area of intelligent systems. Covering major European projects paving the way to a serious smart / intelligent collaboration, the chapters explore e.g. cyber-security issues, 3D digitization, aerial robots, and SMEs that have introduced cyber-physical production systems. Taken together, they offer unique insights into contemporary artificial intelligence and its potential for innovation.

Computational intelligence. --- Neural networks (Computer science) . --- Computational Intelligence. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Intelligence, Computational --- Neural networks (Computer science).

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This book provides a collection of selected papers presented at the International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2019), which was held in Goa, India, on 16–17 August 2019. It covers the latest research trends and advances in the areas of data science, artificial intelligence, neural networks, cognitive science and machine learning applications, cyber-physical systems, and cybernetics.

Computational intelligence. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Machine learning. --- Neural networks (Computer science) . --- Engineering—Data processing. --- Computational Intelligence. --- Machine Learning. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Data Engineering. --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Natural computation --- Learning, Machine --- Machine theory

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This volume discusses the theoretical foundations of a new inter- and intra-disciplinary meta-research discipline, which can be succinctly called cognitive metamathematics, with the ultimate goal of achieving a global instance of concrete Artificial Mathematical Intelligence (AMI). In other words, AMI looks for the construction of an (ideal) global artificial agent being able to (co-)solve interactively formal problems with a conceptual mathematical description in a human-style way. It first gives formal guidelines from the philosophical, logical, meta-mathematical, cognitive, and computational points of view supporting the formal existence of such a global AMI framework, examining how much of current mathematics can be completely generated by an interactive computer program and how close we are to constructing a machine that would be able to simulate the way a modern working mathematician handles solvable mathematical conjectures from a conceptual point of view. The thesis that it is possible to meta-model the intellectual job of a working mathematician is heuristically supported by the computational theory of mind, which posits that the mind is in fact a computational system, and by the meta-fact that genuine mathematical proofs are, in principle, algorithmically verifiable, at least theoretically. The introduction to this volume provides then the grounding multifaceted principles of cognitive metamathematics, and, at the same time gives an overview of some of the most outstanding results in this direction, keeping in mind that the main focus is human-style proofs, and not simply formal verification. The first part of the book presents the new cognitive foundations of mathematics’ program dealing with the construction of formal refinements of seminal (meta-)mathematical notions and facts. The second develops positions and formalizations of a global taxonomy of classic and new cognitive abilities, and computational tools allowing for calculation of formal conceptual blends are described. In particular, a new cognitive characterization of the Church-Turing Thesis is presented. In the last part, classic and new results concerning the co-generation of a vast amount of old and new mathematical concepts and the key parts of several standard proofs in Hilbert-style deductive systems are shown as well, filling explicitly a well-known gap in the mechanization of mathematics concerning artificial conceptual generation.

Computer science—Mathematics. --- Computer mathematics. --- Neural networks (Computer science) . --- Mathematical Applications in Computer Science. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Computer mathematics --- Electronic data processing --- Mathematics --- Computer science --- Neural networks (Computer science) --- Mathematics.