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This book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of deep learning models, with a focus on neural network …
This book is a rigorous but practical presentation of the techniques of uncertainty quantification, with applications in R and Python. This volume includes mathematical arguments …
This book is the first comprehensive guide to logic-based Benders decomposition (LBBD), a general and versatile method for breaking large, complex optimization problems into …
This proceedings volume presents new methods and applications in Operational Research and Management Science with a special focus on Business Analytics. Featuring selected …
Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and …
This book introduces the fundamentals of probability, statistical, and reliability concepts, the classical methods of uncertainty quantification and analytical reliability …
This book deals with an often-neglected feature of location problems, namely uncertainty, by combining two related fields: location theory and optimization. Written by leading …
This book aims at an innovative approach within the framework of convex analysis and optimization, based on an in-depth study of the behavior and properties of the supremum of …
In mathematical modeling of processes occurring in logistics, management science, operations research, networks, mathematical finance, medicine, and control theory, one often …
Dieses Buch stellt interdisziplinäre Forschung im Bereich Software-Engineering von Anwendungen für den sozialen Sektor vor. Der Autor konzentriert sich auf Softwareanwendungen, die …