Algorithmic Mathematics
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Probabilistic Methods For Algorithmic Discrete Mathematics
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Author : Michel Habib
language : en
Publisher: Springer Science & Business Media
Release Date : 1998-08-19
Probabilistic Methods For Algorithmic Discrete Mathematics written by Michel Habib and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-08-19 with Computers categories.
The book gives an accessible account of modern pro- babilistic methods for analyzing combinatorial structures and algorithms. Each topic is approached in a didactic manner but the most recent developments are linked to the basic ma- terial. Extensive lists of references and a detailed index will make this a useful guide for graduate students and researchers. Special features included: - a simple treatment of Talagrand inequalities and their applications - an overview and many carefully worked out examples of the probabilistic analysis of combinatorial algorithms - a discussion of the "exact simulation" algorithm (in the context of Markov Chain Monte Carlo Methods) - a general method for finding asymptotically optimal or near optimal graph colouring, showing how the probabilistic method may be fine-tuned to explit the structure of the underlying graph - a succinct treatment of randomized algorithms and derandomization techniques
Algorithmic Mathematics In Machine Learning
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Author : Bastian Bohn
language : en
Publisher: SIAM
Release Date : 2024-04-08
Algorithmic Mathematics In Machine Learning written by Bastian Bohn and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-08 with Computers categories.
This unique book explores several well-known machine learning and data analysis algorithms from a mathematical and programming perspective. The authors present machine learning methods, review the underlying mathematics, and provide programming exercises to deepen the reader’s understanding; accompany application areas with exercises that explore the unique characteristics of real-world data sets (e.g., image data for pedestrian detection, biological cell data); and provide new terminology and background information on mathematical concepts, as well as exercises, in “info-boxes” throughout the text. Algorithmic Mathematics in Machine Learning is intended for mathematicians, computer scientists, and practitioners who have a basic mathematical background in analysis and linear algebra but little or no knowledge of machine learning and related algorithms. Researchers in the natural sciences and engineers interested in acquiring the mathematics needed to apply the most popular machine learning algorithms will also find this book useful. This book is appropriate for a practical lab or basic lecture course on machine learning within a mathematics curriculum.
Algorithmic Mathematics
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Author : Stefan Hougardy
language : en
Publisher: Springer
Release Date : 2016-10-14
Algorithmic Mathematics written by Stefan Hougardy and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-14 with Computers categories.
Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.
Discrete Algorithmic Mathematics Third Edition
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Author : Stephen B. Maurer
language : en
Publisher: CRC Press
Release Date : 2005-01-21
Discrete Algorithmic Mathematics Third Edition written by Stephen B. Maurer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-21 with Mathematics categories.
Thoroughly revised for a one-semester course, this well-known and highly regarded book is an outstanding text for undergraduate discrete mathematics. It has been updated with new or extended discussions of order notation, generating functions, chaos, aspects of statistics, and computational biology. Written in a lively, clear style that talks to the reader, the book is unique for its emphasis on algorithmics and the inductive and recursive paradigms as central mathematical themes. It includes a broad variety of applications, not just to mathematics and computer science, but to natural and social science as well. A manual of selected solutions is available for sale to students; see sidebar. A complete solution manual is available free to instructors who have adopted the book as a required text.
Algorithmic And High Frequency Trading
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Author : Álvaro Cartea
language : en
Publisher: Cambridge University Press
Release Date : 2015-08-06
Algorithmic And High Frequency Trading written by Álvaro Cartea and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-06 with Business & Economics categories.
A straightforward guide to the mathematics of algorithmic trading that reflects cutting-edge research.
Discrete Algorithmic Mathematics
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Author : Stephen B. Maurer
language : en
Publisher: CRC Press
Release Date : 2005-01-21
Discrete Algorithmic Mathematics written by Stephen B. Maurer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-21 with Computers categories.
Thoroughly revised for a one-semester course, this well-known and highly regarded book is an outstanding text for undergraduate discrete mathematics. It has been updated with new or extended discussions of order notation, generating functions, chaos, aspects of statistics, and computational biology. Written in a lively, clear style, the book is unique in its emphasis on algorithmics and the inductive and recursive paradigms as central mathematical themes. It includes a broad variety of applications, not just to mathematics and computer science, but to natural and social science as well.
Discrete Algorithmic Mathematics Second Edition
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Author : Stephen B. Maurer
language : en
Publisher: A K Peters/CRC Press
Release Date : 1998
Discrete Algorithmic Mathematics Second Edition written by Stephen B. Maurer and has been published by A K Peters/CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Mathematics categories.
What is discrete algorithmic mathematics. Mathematical preliminaries. Algorithms. Mathematical induction. Graphs and trees. Fundamental counting methods. Difference equations. Probability. An introduction to mathematical logic. Algorithmic linear algebra. Infinite processes in discrete mathematics. Sorting things out with sorting.
Combinatorial And Algorithmic Mathematics
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Author : Baha Alzalg
language : en
Publisher: John Wiley & Sons
Release Date : 2024-10-21
Combinatorial And Algorithmic Mathematics written by Baha Alzalg and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-21 with Technology & Engineering categories.
Detailed review of optimization from first principles, supported by rigorous math and computer science explanations and various learning aids Supported by rigorous math and computer science foundations, Combinatorial and Algorithmic Mathematics: From Foundation to Optimization provides a from-scratch understanding to the field of optimization, discussing 70 algorithms with roughly 220 illustrative examples, 160 nontrivial end-of-chapter exercises with complete solutions to ensure readers can apply appropriate theories, principles, and concepts when required, and Matlab codes that solve some specific problems. This book helps readers to develop mathematical maturity, including skills such as handling increasingly abstract ideas, recognizing mathematical patterns, and generalizing from specific examples to broad concepts. Starting from first principles of mathematical logic, set-theoretic structures, and analytic and algebraic structures, this book covers both combinatorics and algorithms in separate sections, then brings the material together in a final section on optimization. This book focuses on topics essential for anyone wanting to develop and apply their understanding of optimization to areas such as data structures, algorithms, artificial intelligence, machine learning, data science, computer systems, networks, and computer security. Combinatorial and Algorithmic Mathematics includes discussion on: Propositional logic and predicate logic, set-theoretic structures such as sets, relations, and functions, and basic analytic and algebraic structures such as sequences, series, subspaces, convex structures, and polyhedra Recurrence-solving techniques, counting methods, permutations, combinations, arrangements of objects and sets, and graph basics and properties Asymptotic notations, techniques for analyzing algorithms, and computational complexity of various algorithms Linear optimization and its geometry and duality, simplex and non-simplex algorithms for linear optimization, second-order cone programming, and semidefinite programming Combinatorial and Algorithmic Mathematics is an ideal textbook resource on the subject for students studying discrete structures, combinatorics, algorithms, and optimization. It also caters to scientists across diverse disciplines that incorporate algorithms and academics and researchers who wish to better understand some modern optimization methodologies.
Algorithmic Graph Theory And Perfect Graphs
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Author : Martin Charles Golumbic
language : en
Publisher: Elsevier
Release Date : 2004-02-04
Algorithmic Graph Theory And Perfect Graphs written by Martin Charles Golumbic and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-02-04 with Mathematics categories.
Algorithmic Graph Theory and Perfect Graphs, first published in 1980, has become the classic introduction to the field. This new Annals edition continues to convey the message that intersection graph models are a necessary and important tool for solving real-world problems. It remains a stepping stone from which the reader may embark on one of many fascinating research trails. The past twenty years have been an amazingly fruitful period of research in algorithmic graph theory and structured families of graphs. Especially important have been the theory and applications of new intersection graph models such as generalizations of permutation graphs and interval graphs. These have lead to new families of perfect graphs and many algorithmic results. These are surveyed in the new Epilogue chapter in this second edition. - New edition of the "Classic" book on the topic - Wonderful introduction to a rich research area - Leading author in the field of algorithmic graph theory - Beautifully written for the new mathematician or computer scientist - Comprehensive treatment
Algorithmic Algebraic Number Theory
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Author : M. Pohst
language : en
Publisher: Cambridge University Press
Release Date : 1997-09-25
Algorithmic Algebraic Number Theory written by M. Pohst and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-09-25 with Mathematics categories.
Now in paperback, this classic book is addresssed to all lovers of number theory. On the one hand, it gives a comprehensive introduction to constructive algebraic number theory, and is therefore especially suited as a textbook for a course on that subject. On the other hand many parts go beyond an introduction an make the user familliar with recent research in the field. For experimental number theoreticians new methods are developed and new results are obtained which are of great importance for them. Both computer scientists interested in higher arithmetic and those teaching algebraic number theory will find the book of value.