Posted by **naag** at March 22, 2017

English | ISBN: 0199456666 | 2015 | 692 pages | EPUB | 27 MB

Algorithms: Design and Analysis of is a textbook designed for the undergraduate and postgraduate students of computer science engineering, information technology, and computer applications. It helps the students to understand the fundamentals and applications of algorithms.

Posted by **nebulae** at Feb. 7, 2017

English | ISBN: 0199456666 | 2015 | 692 pages | PDF | 66 MB

Posted by **roxul** at May 23, 2016

English | ISBN: 0199456666 | 2015 | 692 pages | PDF | 66 MB

Posted by **ParRus** at May 3, 2015

English | MP4 + PDF slides | 960 x 540 | AVC ~22.2 kbps | 15 fps

AAC | 128 Kbps | 44.1 KHz | 2 channels | Subs: English (srt) | ~19 hours | 1.24 GB

AAC | 128 Kbps | 44.1 KHz | 2 channels | Subs: English (srt) | ~19 hours | 1.24 GB

In this course you will learn several fundamental principles of algorithm design. You'll learn the divide-and-conquer design paradigm, with applications to fast sorting, searching, and multiplication. You'll learn several blazingly fast primitives for computing on graphs, such as how to compute connectivity information and shortest paths. Finally, we'll study how allowing the computer to "flip coins" can lead to elegant and practical algorithms and data structures.

Posted by **ParRus** at June 6, 2013

English | MP4 | 960 x 540 | AVC ~22.1 kbps | 15 fps

AAC | 122 Kbps | 44.1 KHz | 2 channels | Subs: English (srt) | 19:04:49 | 1.52 GB

AAC | 122 Kbps | 44.1 KHz | 2 channels | Subs: English (srt) | 19:04:49 | 1.52 GB

In this course you will learn several fundamental principles of advanced algorithm design. You'll learn the greedy algorithm design paradigm, with applications to computing good network backbones (i.e., spanning trees) and good codes for data compression. You'll learn the tricky yet widely applicable dynamic programming algorithm design paradigm, with applications to routing in the Internet and sequencing genome fragments.

Posted by **house23** at April 11, 2013

MP4 | AVC 21kbps | English | 960x540 | 15fps | 19 hours | AAC stereo 114kbps | 1.24 GB

In this course you will learn several fundamental principles of algorithm design. You'll learn the divide-and-conquer design paradigm, with applications to fast sorting, searching, and multiplication. You'll learn several blazingly fast primitives for computing on graphs, such as how to compute connectivity information and shortest paths. Finally, we'll study how allowing the computer to "flip coins" can lead to elegant and practical algorithms and data structures. Learn the answers to questions such as: How do data structures like heaps, hash tables, bloom filters, and balanced search trees actually work, anyway? How come QuickSort runs so fast? What can graph algorithms tell us about the structure of the Web and social networks? Did my 3rd-grade teacher explain only a suboptimal algorithm for multiplying two numbers?

Posted by **ChrisRedfield** at Dec. 2, 2015

Published: 2011-11-17 | ISBN: 1461417007 | PDF | 440 pages | 2.87 MB

Posted by **nebulae** at Feb. 21, 2017

English | ISBN: 027376411X | 2012 | 592 pages | PDF | 2 MB

Posted by **ChrisRedfield** at Feb. 10, 2017

Published: 2006-02-24 | ISBN: 0321358287, 0321364139 | PDF | 592 pages | 19.14 MB

Posted by **ph4rr3l** at Dec. 26, 2013

Published: November 18, 2011 | ISBN: 1461417007 | PDF | 451 pages | 3 MB

When precise algorithmic solutions are difficult to compute, the use of approximation algorithms can help. Design and Analysis of Approximation Algorithms is a textbook for a graduate course in theoretical computer science taught globally in universities. It can also be used as a reference work for researchers in the area of design and analysis algorithms. There are few texts available for this standard course, and those that do exist mainly follow a problem-oriented format. This text follows a structured, technique-oriented presentation. Approximation algorithms are organized into chapters based on the design techniques for the algorithms, enabling the reader to study algorithms of the same nature with ease, and providing an improved understanding of the design and analysis techniques for approximation algorithms. Instructors benefit from this approach allowing for an easy way to present the ideas and techniques of algorithms with a unified approach.