Introduction to algorithms - Info and Reading Options
By Thomas H. Cormen, Charles Eric Leiserson, Ronald L. Rivest, Clifford Stein and EBSCOhost
"Introduction to algorithms" was published by MIT Press, in 2009 - Massachusetts - Cambridge, Mass., the book is classified in bibliography genre, it has 1 pages and the language of the book is English.
“Introduction to algorithms” Metadata:
- Title: Introduction to algorithms
- Authors: Thomas H. CormenCharles Eric LeisersonRonald L. RivestClifford SteinEBSCOhost
- Language: English
- Number of Pages: 1
- Publisher: MIT Press,
- Publish Date: 2009
- Publish Location: ➤ Massachusetts - Cambridge, Mass.
- Genres: bibliography
- Dewey Decimal Classification: 005.1
- Library of Congress Classification: QA76.6 .C662 2009
“Introduction to algorithms” Subjects and Themes:
- Subjects: ➤ Computer programming - Computer algorithms - Bilgasayar programlama - Bilgisayar algoritmaları - COMPUTERS - Software Development & Engineering - General - Programming - Open Source - Tools - Algorithmische Programmierung - Algorithmentheorie - Algoritmen - Algorithmus - Datenstruktur - Datoralgoritmer - Datastrukturer
Edition Specifications:
- Number of Pages: ➤ 1 online resource (xix, 1292 pages) : illustrations.
Edition Identifiers:
- Online Computer Library Center (OCLC) ID: 676697295
- ISBN-13: 9780262270830
- All ISBNs: ➤ 9780262270830 - 0262270838 - 9780262033848 - 0262033844 - 9780262533058 - 0262533057
AI-generated Review of “Introduction to algorithms”:
"Introduction to algorithms" Table Of Contents:
- 1- I. Foundations. The role of algorithms in computing
- 2- Getting started
- 3- Growth of functions
- 4- Divide
- 5- nd
- 6- onquer
- 7- Probabilistic analysis and randomized algorithms
- 8- II. Sorting and order statistics. Heapsort
- 9- Quicksort
- 10- Sorting in linear time
- 11- Medians and order statistics
- 12- III. Data structures. Elementary data structures
- 13- Hash tables
- 14- Binary search trees
- 15- Red
- 16- lack trees
- 17- Augmenting data structures
- 18- IV. Advanced design and analysis techniques. Dynamic programming
- 19- Greedy algorithms
- 20- Amortized analysis
- 21- V. Advanced data structures. B
- 22- rees
- 23- Fibonacci heaps
- 24- van Emde Boas trees
- 25- Data structures for disjoint sets
- 26- VI. Graph algorithms. Elementary graph algorithms
- 27- Minimum spanning trees
- 28- Single
- 29- ource shortest paths
- 30- All
- 31- airs shortest paths
- 32- Maximun flow
- 33- VII. Selected topics. Multithreaded algorithms
- 34- Matrix operations
- 35- Linear programming
- 36- Polynomials and the FFT
- 37- Number
- 38- heoretic algorithms
- 39- String matching
- 40- Computational geometry
- 41- NP
- 42- ompleteness
- 43- Approximation algorithms
- 44- VIII. Appendix: Mathematical background. Summations
- 45- Sets, etc.
- 46- Counting and probability
- 47- Matrices.
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