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This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Pre...
"Graphs. Such a simple idea. Map a problem onto a graph then solve it by searching over the graph or by exploring the structure of the graph. What could be easier? Turns out, however, that working with graphs is a vast and complex field. Keeping up is challenging. To help keep up, you just need an editor who knows most people working with graphs, and have that editor gather nearly 70 researchers to summarize their work with graphs. The result is the book Massive Graph Analytics." — Timothy G. Mattson, Senior Principal Engineer, Intel Corp Expertise in massive-scale graph analytics is key for solving real-world grand challenges from healthcare to sustainability to detecting insider threats, cyber defense, and more. This book provides a comprehensive introduction to massive graph analytics, featuring contributions from thought leaders across academia, industry, and government. Massive Graph Analytics will be beneficial to students, researchers, and practitioners in academia, national laboratories, and industry who wish to learn about the state-of-the-art algorithms, models, frameworks, and software in massive-scale graph analytics.
BOOK OF ABSTRACTS CHAOS 2016 Chaotic Modeling and Simulation International Conference London, U.K., 23-26 May 2016
Applied Mathematics with Open-source Software: Operational Research Problems with Python and R is aimed at a broad segment of readers who wish to learn how to use open-source software to solve problems in applied mathematics. The book has an innovative structure with 4 sections of two chapters covering a large range of applied mathematical techniques: probabilistic modelling, dynamical systems, emergent behaviour and optimisation. The pairs of chapters in each section demonstrate different families of solution approaches. Each chapter starts with a problem, gives an overview of the relevant theory, shows a solution approach in R and in Python, and finally gives wider context by including a n...
This comprehensive book brings together research published during 2021 analysing the impact of the Covid-19 pandemic on the economy – on output and employment, on inequality, and on public policy responses. The Covid-19 pandemic has been the greatest public health crisis for a century – since the ‘Spanish Flu’ pandemic of 1919. The economic impact has been equally seismic. While it is too early to measure the full economic cost – since much of this will continue to accumulate for some time to come – it will certainly be one of the greatest global economic shocks of the past century. Some chapters in this edited volume report on specific countries, while some take a comparative lo...
Gathering the proceedings of the 11th CHAOS2018 International Conference, this book highlights recent developments in nonlinear, dynamical and complex systems. The conference was intended to provide an essential forum for Scientists and Engineers to exchange ideas, methods, and techniques in the field of Nonlinear Dynamics, Chaos, Fractals and their applications in General Science and the Engineering Sciences. The respective chapters address key methods, empirical data and computer techniques, as well as major theoretical advances in the applied nonlinear field. Beyond showcasing the state of the art, the book will help academic and industrial researchers alike apply chaotic theory in their studies.