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Authors: Leonid Berlyand; PierreEmmanuel Jabin. (2023)  The goal of this book is to provide a mathematical perspective on some key elements of the socalled deep neural networks (DNNs). Much of the interest in deep learning has focused on the implementation of DNNbased algorithms. Our hope is that this compact textbook will offer a complementary point of view that emphasizes the underlying mathematical ideas.

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Authors: Philipp Grohs (2023)  This book presents the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field. It serves both as a starting point for researchers and graduate students in computer science, mathematics, and statistics trying to get into the field and as an invaluable reference for future research

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Authors: Richard J. Larsen (2013)  The authors demonstrate how and when to use statistical methods, while reinforcing the calculus that students have mastered in previous courses. Throughout theFifth Edition, the authors have added and updated examples and case studies, while also refining existing features that show a clear path from theory to practice.

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Authors: Anne M. Cooper (2023)  The marketing world has long underappreciated the buying power held by adults over 65 years of age. In the current age of longevity, it's essential that students engage with strategies that embrace all age groups. This text combines professional interviews, theorybased research, and practical exercises to supplement any strategic comm course

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Authors: Michael Gr. Voskoglou (2020)  The present book contains 20 articles collected from amongst the 53 total submitted manuscripts for the Special Issue “Fuzzy Sets, Fuzzy Loigic and Their Applications” of the MDPI journal Mathematics. The articles, which appear in the book in the series in which they were accepted, published in Volumes 7 (2019) and 8 (2020) of the journal, cover a wide range of topics connected to the theory and applications of fuzzy systems and their extensions and generalizations.

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Authors: William W. Cooper (2000)  Each chapter accompanies its developments with simple numerical examples and discussions of actual applications. Emphasis is placed on the use as well as an understanding of DEA and the topics in this book have been selected and treated accordingly. The objective is to introduce students, researchers, and practitioners in business, economics, engineering, and the sciences to Data Envelopment Analysis.

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Authors: H.J. Zimmermann (1996)  Fuzzy Set Theory  And Its Applications, Third Edition is a textbook for courses in fuzzy set theory. It can also be used as an introduction to the subject. The character of a textbook is balanced with the dynamic nature of the research in the field by including many useful references to develop a deeper understanding among interested readers.

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Authors: HansJürgen Zimmermann (2012)  This introduction to fuzzy set theory and its multitude of applications seeks to balance the character of the book with the dynamic nature of the research. This edition includes new chapters on possibility theory, fuzzy logic and approximate reasoning, expert systems, fuzzy control, fuzzy data analysis, decision making and fuzzy set models in operations research. Existing material has been updated, and extended exercises are included.

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Authors: George J. Klir (1995)  

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Authors: George B. Arfken (2001)  Arfken and Weber's bestselling Mathematical Methods for Physicists has provided upperlevel undergraduate and graduate students with the paramount coverage of the mathematics necessary for advanced study in physics and engineering. It provides the essential mathematical methods that aspiring physicists are likely to encounter as students or beginning researchers.

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Authors: Jagdev Singh (2022)  This book contains several contemporary topics in the areas of mathematical modelling and computation for complex systems. The readers find several new mathematical methods, mathematical models and computational techniques having significant relevance in studying various complex systems.

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Authors: Daniel Bienstock (2004)  This volume contains the papers accepted for publication at IPCO X, the Tenth InternationalConferenceonInteger ProgrammingandCombinatorialOptimi tion, held in New York City, New York, USA, June 711, 2004.The IPCO series of conferences presents recent results in theory, computation and applications of integer programming and combinatorial optimization.

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Authors: Bernhard Korte (2012)  This fifth edition has again been updated, revised, and significantlyextended, with more than 60 new exercises and new material on varioustopics, including Cayley's formula, blocking flows, faster"b"matching separation, multidimensional knapsack, multicommoditymaxflow mincut ratio, and sparsest cut. Thus, this book represents the state of the art of combinatorial optimization.

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Authors: Barnabas Bede (2013)  This book presents a mathematicallybased introduction into the fascinating topic of Fuzzy Sets and Fuzzy Logic and might be used as textbook at both undergraduate and graduate levels and also as reference guide for mathematician, scientists or engineers who would like to get an insight into Fuzzy Logic. Fuzzy Sets have been introduced by Lotfi Zadeh in 1965 and since then, they have been used in many applications. As a consequence, there is a vast literature on the practical applications of fuzzy sets, while theory has a more modest coverage

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Authors: Lekh Raj Vermani (2019)  This book introduces a set of concepts in solving problems computationally such as Growth of Functions; Backtracking; Divide and Conquer; Greedy Algorithms; Dynamic Programming; Elementary Graph Algorithms; Minimal Spanning Tree; SingleSource Shortest Paths; All Pairs Shortest Paths; Flow Networks; Polynomial Multiplication, to ways of solving NPComplete Problems, supported with comprehensive, and detailed problems and solutions, making it an ideal resource to those studying computer science, computer engineering and information technology.

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Authors: George Casella (2002)  This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts

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Authors: Paul C. Cozby (2011)  Highlights of the new edition include a broader introduction of different research techniques in Chapter 4, extensive revision of the 'validity of measurements' section, and updated structural equations models.

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Authors: Neal Koblitz (1998)  From the reviews: "This is a textbook in cryptography with emphasis on algebraic methods. It is supported by many exercises (with answers) making it appropriate for a course in mathematics or computer science. [...] Overall, this is an excellent expository text, and will be very useful to both the student and researcher." Mathematical Reviews

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Authors: Michio Masujima (2005)  Throughout the book, the author presents over 150 problems and exercises  many from such branches of physics as quantum mechanics, quantum statistical mechanics, and quantum field theory  together with outlines of the solutions in each case. Detailed solutions are given, supplementing the materials discussed in the main text, allowing problems to be solved making direct use of the method illustrated.

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Authors: John Lawrence Nazareth (2023)  Numerical Algorithmic Science and Engineering (NAS&E), or more compactly, Numerical Algorithmics, is the theoretical and empirical study and the practical implementation and application of algorithms for solving finitedimensional problems of a numeric nature
