A Note On Enumeration Methods For The Mean Value Analysis Algorithm PDF Download

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DESIGN AND ANALYSIS OF ALGORITHMS, 2nd Ed

DESIGN AND ANALYSIS OF ALGORITHMS, 2nd Ed
Author: PANNEERSELVAM, R.
Publisher: PHI Learning Pvt. Ltd.
Total Pages: 642
Release: 2016
Genre: Computers
ISBN: 8120351649

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This highly structured text, in its second edition, provides comprehensive coverage of design techniques of algorithms. It traces the complete development of various algorithms in a stepwise approach followed by their pseudo-codes to build an understanding of their applications in practice. With clear explanations, the textbook intends to be much more comprehensive book on design and analysis of algorithm. Commencing with the introduction, the book gives a detailed account of graphs and data structure. It then elaborately discusses the matrix algorithms, basic algorithms, network algorithms, sorting algorithm, backtracking algorithms and search algorithms. The text also focuses on the heuristics, dynamic programming and meta heuristics. The concepts of cryptography and probabilistic algorithms have been described in detail. Finally, the book brings out the underlying concepts of benchmarking of algorithms, algorithms to schedule processor(s) and complexity of algorithms. New to the second Edition New chapters on • Matrix algorithms • Basic algorithms • Backtracking algorithms • Complexity of algorithms Several new sections including asymptotic notation, amortized analysis, recurrences, balanced trees, skip list, disjoint sets, maximal flow algorithm, parsort, radix sort, selection sort, topological sorting/ordering, median and ordered statistics, Huffman coding algorithm, transportation problem, heuristics for scheduling, etc., have been incorporated into the text.


Applied Algebra, Algebraic Algorithms and Error-Correcting Codes

Applied Algebra, Algebraic Algorithms and Error-Correcting Codes
Author: Llorenc Huguet
Publisher: Springer Science & Business Media
Total Pages: 428
Release: 1989-06-14
Genre: Computers
ISBN: 9783540510826

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The present volume contains the proceedings of the AAECC-5 Conference held at Menorca (Balearic Islands), June 15-19, 1987. The annual International AAECC Conference covers a range of topics related to Applied Algebra, Error-Correcting Codes, Finite Algebraic Structures, Computational Methods and Complexity in Algebra and Geometry. For the AAECC-5 Conference 73 papers were presented. Out of these thirty papers were selected for publication in the proceedings. They deal with topics such as error correcting codes (concerning problems of covering radius, decoding methods, expert systems and general results in coding theory), computational algebra, Gröbner basis, complexity, finite algebra and graphs. The proceedings of the 6th conference are published as Vol. 357 of the Lecture Notes in Computer Science.


Machine Learning, Optimization, and Data Science

Machine Learning, Optimization, and Data Science
Author: Giuseppe Nicosia
Publisher: Springer Nature
Total Pages: 667
Release: 2022-02-01
Genre: Computers
ISBN: 3030954676

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This two-volume set, LNCS 13163-13164, constitutes the refereed proceedings of the 7th International Conference on Machine Learning, Optimization, and Data Science, LOD 2021, together with the first edition of the Symposium on Artificial Intelligence and Neuroscience, ACAIN 2021. The total of 86 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 215 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.


Analytic Combinatorics

Analytic Combinatorics
Author: Philippe Flajolet
Publisher: Cambridge University Press
Total Pages: 825
Release: 2009-01-15
Genre: Mathematics
ISBN: 1139477161

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Analytic combinatorics aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the analysis of algorithms and for the study of scientific models in many disciplines, including probability theory, statistical physics, computational biology, and information theory. With a careful combination of symbolic enumeration methods and complex analysis, drawing heavily on generating functions, results of sweeping generality emerge that can be applied in particular to fundamental structures such as permutations, sequences, strings, walks, paths, trees, graphs and maps. This account is the definitive treatment of the topic. The authors give full coverage of the underlying mathematics and a thorough treatment of both classical and modern applications of the theory. The text is complemented with exercises, examples, appendices and notes to aid understanding. The book can be used for an advanced undergraduate or a graduate course, or for self-study.


An Introduction to Statistical Analysis of Random Arrays

An Introduction to Statistical Analysis of Random Arrays
Author: V. L. Girko
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 700
Release: 2018-11-05
Genre: Mathematics
ISBN: 3110916681

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Spectral Algorithms

Spectral Algorithms
Author: Ravindran Kannan
Publisher: Now Publishers Inc
Total Pages: 153
Release: 2009
Genre: Computers
ISBN: 1601982747

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Spectral methods refer to the use of eigenvalues, eigenvectors, singular values and singular vectors. They are widely used in Engineering, Applied Mathematics and Statistics. More recently, spectral methods have found numerous applications in Computer Science to "discrete" as well as "continuous" problems. Spectral Algorithms describes modern applications of spectral methods, and novel algorithms for estimating spectral parameters. The first part of the book presents applications of spectral methods to problems from a variety of topics including combinatorial optimization, learning and clustering. The second part of the book is motivated by efficiency considerations. A feature of many modern applications is the massive amount of input data. While sophisticated algorithms for matrix computations have been developed over a century, a more recent development is algorithms based on "sampling on the fly" from massive matrices. Good estimates of singular values and low rank approximations of the whole matrix can be provably derived from a sample. The main emphasis in the second part of the book is to present these sampling methods with rigorous error bounds. It also presents recent extensions of spectral methods from matrices to tensors and their applications to some combinatorial optimization problems.