Showing posts with label Algorithms. Show all posts
Showing posts with label Algorithms. Show all posts

Wednesday, 9 February 2011

Graphs & Digraphs, Third Edition



Graphs & Digraphs, Third Edition
Gary Chartrand | 1996-08-01 00:00:00 | Springer | 432 | Algorithms
This is the third edition of the popular text on graph theory. As in previous editions, the text presents graph theory as a mathematical discipline and emphasizes clear exposition and well written proofs. New in this edition are expanded treatments of graph decomposition and external graph theory, a study of graph vulnerability and domination, and introductions to voltage graphs, graph labelings, and the probabilistic method in graph theory.
Reviews
While I won't argue that the book is thorough and professional, I find it lacking enough examples to let me comprehensively understand the material. In many books, the author will introduce a concept and then give examples to cement the application of these concepts within the chapter text and/or figures. Chartrand and Lesniak use such examples very sparingly, and often for the more mundane concepts that need no additional illustration. In the first few chapters, where a great amount of terminology is introduced, these examples would have been extremely useful to ensure that the reader has a firm grasp on the basics. Instead, I found myself confused in later chapters because I had misunderstood one of the more fundamental concepts. I rarely, if ever, have this problem with a book includes sufficient examples.



While those more versed in graph theory might prefer a book with less example "fluff", someone just getting into the topic really should look elsewhere to ensure themselves a more stable and confident foundation.
Reviews
This was the one book assigned for a class where I did NOT have to go out and buy a few other books in order to round out the assigned text. Chartrand has written books on graph theory directed at students of many different levels, and this one is advanced -- but the keynote attribute of this book its thoroughness and accuracy. The proofs depend upon appropriate use of accurate definitions, and here the definitions are VERY clear and specific -- therefore in constructing the proofs in the exercises the student really comes to understand the meaning of the definitions and the concepts they describe. At first I thought this book was going to be unapproachable because it does not kill you with friendly banter, but I have come to appreciate its solid approach and trustworthiness not to lead anyone astray mathematically. By the way, graph theory is really fun. Don't pass us the chance to study it!

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Formal Syntax and Semantics of Programming Languages: A Laboratory Based Approach



Formal Syntax and Semantics of Programming Languages: A Laboratory Based Approach
Kenneth Slonneger, Barry L. Kurtz | 1994-01-01 00:00:00 | Addison-Wesley Publishing Company | 637 | Algorithms
Presents a panorama of techniques in formal syntax, operational semantics and formal semantics. Includes valuable hands-on laboratory exercises.
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Friday, 28 January 2011

Graph Theory, Combinatorics and Algorithms: Interdisciplinary Applications



Graph Theory, Combinatorics and Algorithms: Interdisciplinary Applications
Martin Charles Golumbic (Editor), Irith Ben-Arroyo Hartman (Editor) | 2005-01-01 00:00:00 | Springer; 1 edition | 292 | Algorithms
Graph Theory, Combinatorics and Algorithms: Interdisciplinary Applications focuses on discrete mathematics and combinatorial algorithms interacting with real world problems in computer science, operations research, applied mathematics and engineering. The book contains eleven chapters written by experts in their respective fields, and covers a wide spectrum of high-interest problems across these discipline domains. Among the contributing authors are Richard Karp of UC Berkeley and Robert Tarjan of Princeton; both are at the pinnacle of research scholarship in Graph Theory and Combinatorics. The chapters from the contributing authors focus on "real world" applications, all of which will be of considerable interest across the areas of Operations Research, Computer Science, Applied Mathematics, and Engineering. These problems include Internet congestion control, high-speed communication networks, multi-object auctions, resource allocation, software testing, data structures, etc. In sum, this is a book focused on major, contemporary problems, written by the top research scholars in the field, using cutting-edge mathematical and computational techniques.
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Tuesday, 25 January 2011

Learning Theory: An Approximation Theory Viewpoint (Cambridge Monographs on Applied and Computational Mathematics)



Learning Theory: An Approximation Theory Viewpoint (Cambridge Monographs on Applied and Computational Mathematics)
Felipe Cucker,Ding Xuan Zhou | 2007-05-14 00:00:00 | Cambridge University Press | 236 | Algorithms
The goal of learning theory is to approximate a function from sample values. To attain this goal learning theory draws on a variety of diverse subjects, specifically statistics, approximation theory, and algorithmics. Ideas from all these areas blended to form a subject whose many successful applications have triggered a rapid growth during the last two decades. This is the first book to give a general overview of the theoretical foundations of the subject emphasizing the approximation theory, while still giving a balanced overview. It is based on courses taught by the authors, and is reasonably self-contained so will appeal to a broad spectrum of researchers in learning theory and adjacent fields. It will also serve as an introduction for graduate students and others entering the field, who wish to see how the problems raised in learning theory relate to other disciplines.

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Saturday, 22 January 2011

Optimization Algorithms for Networks and Graphs, Second Edition



Optimization Algorithms for Networks and Graphs, Second Edition
James Evans | 1992-01-01 00:00:00 | CRC; 2 edition | 488 | Algorithms
A revised and expanded advanced-undergraduate/graduate text (first ed., 1978) about optimization algorithms for problems that can be formulated on graphs and networks. This edition provides many new applications and algorithms while maintaining the classic foundations on which contemporary algorithm.

Review
...a must for the student with an interest in network optimization and a valuable addition to the library of any researcher in the area.
---Interfaces
Includes new material based on developments since the First Edition, a new chapter on computer representation of graphs and computational complexity issues, and a software (NETSOLVE) for IBM PCs and compatibles.
---The American Mathematical Monthly
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Tuesday, 11 January 2011

Statistical Analysis with R



Statistical Analysis with R
John M. Quick | 2010-10-26 00:00:00 | Packt Publishing | 300 | Algorithms
This is a practical, step by step guide that will help you to quickly become proficient in the data analysis using R. The book is packed with clear examples, screenshots, and code to carry on your data analysis without any hurdle. If you are a data analyst, business or information technology professional, student, educator, researcher, or anyone else who wants to learn to analyze the data effectively then this book is for you. No prior experience with R is necessary. Knowledge of other programming languages, software packages, or statistics may be helpful, but is not required.

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