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Author: Catherine C. McGeoch
Publisher:
Published: 2012
Total Pages: 272
ISBN-13: 9781139222419
DOWNLOAD EBOOK →This guidebook is for those who want to use computational experiments to support their work in algorithm design and analysis.
Author: Catherine C. McGeoch
Publisher: Cambridge University Press
Published: 2012-01-30
Total Pages: 273
ISBN-13: 1107001730
DOWNLOAD EBOOK →This is a guidebook for those who want to use computational experiments to support their work in algorithm design and analysis. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered so that the book can be used by anyone who has taken a course or two in data structures and algorithms.
Author: Rudolf Fleischer
Publisher: Springer
Published: 2003-07-01
Total Pages: 286
ISBN-13: 3540363831
DOWNLOAD EBOOK →Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications. Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.
Author: Helen C. Purchase
Publisher: Cambridge University Press
Published: 2012-07-23
Total Pages: 263
ISBN-13: 1107010063
DOWNLOAD EBOOK →Takes the human-computer interaction researcher through the complete experimental process, from identifying a research question, to conducting an experiment and analysing the results.
Author: Thomas Bartz-Beielstein
Publisher: Springer Science & Business Media
Published: 2010-11-02
Total Pages: 469
ISBN-13: 3642025382
DOWNLOAD EBOOK →In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on different scenarios of experimental analysis. The first part overviews the main issues in the experimental analysis of algorithms, and discusses the experimental cycle of algorithm development; the second part treats the characterization by means of statistical distributions of algorithm performance in terms of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies. This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment of optimization algorithms and, consequently, their design.
Author: Ed Finn
Publisher: MIT Press
Published: 2017-03-10
Total Pages: 267
ISBN-13: 0262035928
DOWNLOAD EBOOK →The gap between theoretical ideas and messy reality, as seen in Neal Stephenson, Adam Smith, and Star Trek. We depend on—we believe in—algorithms to help us get a ride, choose which book to buy, execute a mathematical proof. It's as if we think of code as a magic spell, an incantation to reveal what we need to know and even what we want. Humans have always believed that certain invocations—the marriage vow, the shaman's curse—do not merely describe the world but make it. Computation casts a cultural shadow that is shaped by this long tradition of magical thinking. In this book, Ed Finn considers how the algorithm—in practical terms, “a method for solving a problem”—has its roots not only in mathematical logic but also in cybernetics, philosophy, and magical thinking. Finn argues that the algorithm deploys concepts from the idealized space of computation in a messy reality, with unpredictable and sometimes fascinating results. Drawing on sources that range from Neal Stephenson's Snow Crash to Diderot's Encyclopédie, from Adam Smith to the Star Trek computer, Finn explores the gap between theoretical ideas and pragmatic instructions. He examines the development of intelligent assistants like Siri, the rise of algorithmic aesthetics at Netflix, Ian Bogost's satiric Facebook game Cow Clicker, and the revolutionary economics of Bitcoin. He describes Google's goal of anticipating our questions, Uber's cartoon maps and black box accounting, and what Facebook tells us about programmable value, among other things. If we want to understand the gap between abstraction and messy reality, Finn argues, we need to build a model of “algorithmic reading” and scholarship that attends to process, spearheading a new experimental humanities.
Author: Gilles Brassard
Publisher: Prentice Hall
Published: 1998
Total Pages: 117
ISBN-13: 9780133599510
DOWNLOAD EBOOK →Author: Catherine C. McGeoch
Publisher: Springer Science & Business Media
Published: 2008-05-08
Total Pages: 371
ISBN-13: 3540685480
DOWNLOAD EBOOK →This book constitutes the refereed proceedings of the 7th International Workshop on Experimental and Efficient Algorithms, WEA 2008, held in Provincetown, MA, USA, in May/June 2008. The 26 revised full papers were carefully reviewed and selected from numerous submissions and present current research on experimental evaluation and engineering of algorithms, as well as in various aspects of computational optimization and its applications. Special focus is put on the use of experimental methods to guide the design, analysis, implementation, and evaluation of algorithms, heuristics, and optimization programs.
Author: George T. Heineman
Publisher: "O'Reilly Media, Inc."
Published: 2008-10-14
Total Pages: 366
ISBN-13: 1449391133
DOWNLOAD EBOOK →Creating robust software requires the use of efficient algorithms, but programmers seldom think about them until a problem occurs. Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs -- with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. With this book, you will: Solve a particular coding problem or improve on the performance of an existing solution Quickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to use Get algorithmic solutions in C, C++, Java, and Ruby with implementation tips Learn the expected performance of an algorithm, and the conditions it needs to perform at its best Discover the impact that similar design decisions have on different algorithms Learn advanced data structures to improve the efficiency of algorithms With Algorithms in a Nutshell, you'll learn how to improve the performance of key algorithms essential for the success of your software applications.
Author: Joachim Gudmundsson
Publisher: Springer
Published: 2014-06-09
Total Pages: 466
ISBN-13: 331907959X
DOWNLOAD EBOOK →This book constitutes the refereed proceedings of the 13th International Symposium on Experimental Algorithms, SEA 2014, held in Copenhagen, Denmark, in June/July 2014. The 36 revised full papers presented together with 3 invited presentations were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on combinatorial optimization, data structures, graph drawing, shortest path, strings, graph algorithms and suffix structures.
