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Introduction To Algorithms is one of the most commonly referred texts when it comes to algorithms, and is used as a textbook in several colleges.
Summary Of The Book
The contemporary study of all computer algorithms can be understood clearly by perusing the contents of Introduction To Algorithms. Although this covers most of the important aspects of algorithms, the concepts have been detailed in a lucid manner, so as to be palatable to readers at all levels of skill.
Introduction To Algorithms has a number of chapters, each of which is self-contained, as it contains an algorithm, followed by a design technique. There is also an area of application or a related topic, so that students can find out the practical implications of the algorithm in question.
There is an introduction unit, where the foundations of algorithms are covered. At all points in the book, the jargon and technical information are presented so as to be readable by anyone who has dabbled to some extent in programming. The foundation unit seeks to enlighten the reader regarding the role algorithms play in modern computer programming and the growth of functions, among other things.
Introduction To Algorithms then moves on to Sorting and Order Statistics, introducing the concepts of Heapsort and Quicksort, and also explaining how to sort in real time. A number of other topics such as Design and Analysis and Graph Algorithms are covered in the book. One feature to note in this book is that two new chapters have been added in this third edition, one on multithreaded algorithms and another on Van Emde Boas trees.
Introduction To Algorithms is a popular book that has sold more than twenty million copies in total. In fact, it is so famous that it is commonly referred to as ‘CLRS’, after the initials of the authors. The book includes new problems and exercises in this edition.
About The Authors
Charles E. Leiserson is a professor at Massachusetts Institute of Technology, in the Electrical Engineering and Computer Science department.
Leiserson is also a Margaret MacVicar Faculty Fellow. He is part of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT and conducts extensive research in the field of computer science.
Thomas H. Cormen is the Professor and Chair in the department of Computer Science at Dartmouth.
He completed his Ph.D from Massachusetts Institute of Technology in 1992, and has been teaching ever since. His research interests include parallel computing and algorithm engineering.
Ronald L. Rivest is a popular cryptographer and he is the Erna Viterbi Professor of Computer Science at Massachusetts Institute of Technology.
Rivest is also a member of the CSAIL, along with Professor Leiserson, and helps draft the guidelines for the Voluntary Voting System for the Election Assistance Commission.
Clifford Stein is the Professor of Computer Science as well as IEOR at Columbia University.
Stein was also chair of the IEOR department for five years from 2008 to 2013, before which he was an Assistant and Associate Professor at Dartmouth College.
1 The Role of Algorithms in Computing
2 Getting Started
3 Growth of Functions
5 Probabilistic Analysis and Randomized Algorithms
II Sorting and Order Statistics
8 Sorting in Linear Time
9 Medians and Order Statistics
III Data Structures
10 Elementary Data Structures
11 Hash Tables
12 Binary Search Trees
13 Red-Black Trees
14 Augmenting Data Structures
IV Advanced Design and Analysis Techniques
15 Dynamic Programming
16 Greedy Algorithms
17 Amortized Analysis
V Advanced Data Structures
19 Fibonacci Heaps
20 Van Emde Boas Trees
21 Data Structures for Disjoint Sets
VI Graph Algorithms
22 Elementary Graph Algorithms
23 Minimum Spanning Trees
24 Single-Source Shortest Paths
25 All-Pairs Shortest Paths
26 Maximum Flow
VII Selected Topics
27 Multithreaded Algorithms
28 Matrix Operations
29 Linear Programming
30 Polynomials and the FFT
31 Number-Theoretic Algorithms
32 String Matching
33 Computational Geometry
35 Approximation Algorithms
VIII Appendix: Mathematical Background
B Sets, Etc.
C Counting and Probability
Good Math is required - Should be patient - Very detail description
20 Dec, 2012
excellent book but not recommended for self learners.
31 Mar, 2015
1 Jan, 2017
Step well taken in right direction
30 Dec, 2014
The Bible of Algorithms
24 Apr, 2014
Cannot be better
17 Apr, 2013
16 Nov, 2011
Expected a better product
12 Jan, 2017
Low quality printing
4 Jan, 2017