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Author: Raj Chandra Bose
Publisher:
ISBN:
Category : Calculators
Languages : en
Pages : 46
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Book Description
This paper established a low upper bound for the number of comparisons required to sort n objects under the condition that the number of permutations be no larger than the number of comparisons.
Author: Raj Chandra Bose
Publisher:
ISBN:
Category : Calculators
Languages : en
Pages : 46
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Book Description
This paper established a low upper bound for the number of comparisons required to sort n objects under the condition that the number of permutations be no larger than the number of comparisons.
Author: William Eric Devanny
Publisher:
ISBN: 9780355309263
Category :
Languages : en
Pages : 108
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Book Description
Sorting is one of the most well studied algorithmic problems in Computer Science. It is a fundamental building block in many other algorithms. In this dissertation, we consider several variants of the classical sorting problem all motivated by modern challenges or technologies. We present algorithms to solve these problem variants and provide lower bounds when possible.The online list labeling problem attempts to maintain integer labels for a dynamic ordered list. As new elements are inserted, old elements may need to be relabeled to make room in the label space. Previous work has looked at minimizing the total number of relabels that need to be performed. However we analyze the version of the problem where the goal is to minimize the maximum number of times any one element is relabeled. We call this the online house numbering problem. This problem is motivated by the modern solid-state memories which have a limited write life. We provide two solutions to the house numbering problem: one that comes within a logarithmic factor of the optimal label space size with optimal maximum relabelings and one that has optimal label space size, but is a logarithmic factor off of the optimal maximum relabelings.Sorting can also mean to split a set of elements into groups of similar elements. Cryptographic handshakes, where two parties securely identify if they belong to a privileged group, motivate studying this form of sorting that we call equivalence class sorting. Instead of sorting with a less-than operator, our goal is to use an = ̄ equivalence relation operator to group a set of elements into their equivalence classes. We prove tight lower bounds that match the run time of previously known algorithms as well as provide algorithms for performing equivalence class sorting in several models of parallel computation.Classical sorting algorithms output the sorted order for a given input list. When the data is continually changing or "evolving", the output of a classical algorithm cannot be guaranteed to be accurate. So we consider a new model for algorithms called the evolving data model. In this model, every time a comparison is performed, two elements that are adjacent in the underlying order are swapped. No algorithm can ever compute the exact correct order of the elements in such an evolving list. Instead the goal is to, over time, converge to be as close to the correct order as possible. We show that simply repeatedly running insertion sort achieves the best possible O( n) inversions relative to the underlying order with exponentially high probability.
Author: James Humboldt Laird
Publisher:
ISBN:
Category : Electronic data processing
Languages : en
Pages :
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Book Description
Author: Bradley N. Miller
Publisher: Franklin Beedle & Associates
ISBN: 9781590282571
Category : Algorithms
Languages : en
Pages : 0
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Book Description
Thes book has three key features : fundamental data structures and algorithms; algorithm analysis in terms of Big-O running time in introducied early and applied throught; pytohn is used to facilitates the success in using and mastering data strucutes and algorithms.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This study is concerned with a sorting problem.
Author: Mahmoud Parsian
Publisher: "O'Reilly Media, Inc."
ISBN: 1491906154
Category : Computers
Languages : en
Pages : 778
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Book Description
If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as building a recommendation system. You’ll learn how to implement the appropriate MapReduce solution with code that you can use in your projects. Dr. Mahmoud Parsian covers basic design patterns, optimization techniques, and data mining and machine learning solutions for problems in bioinformatics, genomics, statistics, and social network analysis. This book also includes an overview of MapReduce, Hadoop, and Spark. Topics include: Market basket analysis for a large set of transactions Data mining algorithms (K-means, KNN, and Naive Bayes) Using huge genomic data to sequence DNA and RNA Naive Bayes theorem and Markov chains for data and market prediction Recommendation algorithms and pairwise document similarity Linear regression, Cox regression, and Pearson correlation Allelic frequency and mining DNA Social network analysis (recommendation systems, counting triangles, sentiment analysis)
Author: R. W. Floyd
Publisher:
ISBN:
Category : Sorting (Electronic computers)
Languages : en
Pages : 20
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Book Description
Comparison/exchange modules can be combined to construct networks capable of sorting elements into nondecreasing order. In the paper one considers combinatorial properties of such networks, and we determine the minimum number of modules required to sort eight or less elements. (Author).
Author: Thomas H Cormen
Publisher: MIT Press
ISBN: 9780262032933
Category : Computers
Languages : en
Pages : 1216
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Book Description
An extensively revised edition of a mathematically rigorous yet accessible introduction to algorithms.
Author: George T. Heineman
Publisher: "O'Reilly Media, Inc."
ISBN: 1449391133
Category : Computers
Languages : en
Pages : 366
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Book Description
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: Geoffrey C. Bowker
Publisher: MIT Press
ISBN: 0262522950
Category : Science
Languages : en
Pages : 390
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Book Description
A revealing and surprising look at how classification systems can shape both worldviews and social interactions. What do a seventeenth-century mortality table (whose causes of death include "fainted in a bath," "frighted," and "itch"); the identification of South Africans during apartheid as European, Asian, colored, or black; and the separation of machine- from hand-washables have in common? All are examples of classification—the scaffolding of information infrastructures. In Sorting Things Out, Geoffrey C. Bowker and Susan Leigh Star explore the role of categories and standards in shaping the modern world. In a clear and lively style, they investigate a variety of classification systems, including the International Classification of Diseases, the Nursing Interventions Classification, race classification under apartheid in South Africa, and the classification of viruses and of tuberculosis. The authors emphasize the role of invisibility in the process by which classification orders human interaction. They examine how categories are made and kept invisible, and how people can change this invisibility when necessary. They also explore systems of classification as part of the built information environment. Much as an urban historian would review highway permits and zoning decisions to tell a city's story, the authors review archives of classification design to understand how decisions have been made. Sorting Things Out has a moral agenda, for each standard and category valorizes some point of view and silences another. Standards and classifications produce advantage or suffering. Jobs are made and lost; some regions benefit at the expense of others. How these choices are made and how we think about that process are at the moral and political core of this work. The book is an important empirical source for understanding the building of information infrastructures.
