Introduction to Algorithms 공부모임

모든 분야에는 기본이 튼튼해야 합니다.
아래의 기술서적은 전기전자공학, 컴퓨터공학, 전산학 분야의 기본이 되는것이고,
학습, 연구, 응용해야할 충분한 가치가 있다고 봅니다.
같이 공부할 분들을 모집합니다.
공부모임에 참가하실 분들은 커널연구회(www.kernel.kr) 게시판에서 참가신청하세요~
지금 바로요~

Introduction to Algorithms, Second Edition

Thomas H. Cormen
Charles E. Leiserson
Ronald L. Rivest
Clifford Stein
The MIT Press
Cambridge , Massachusetts London, England
McGraw-Hill Book Company
Boston Burr Ridge , IL Dubuque , IA Madison , WI New York San Francisco St. Louis
Montréal Toronto

This book is one of a series of texts written by faculty of the Electrical Engineering and
Computer Science Department at the Massachusetts Institute of Technology. It was edited and
produced by The MIT Press under a joint production-distribution agreement with the
McGraw-Hill Book Company.

Copyright © 2001 by The Massachusetts Institute of Technology
First edition 1990

page: 009
Part I: Foundations
Chapter 1: The Role of Algorithms in Computing
Chapter 2: Getting Started
Chapter 3: Growth of Functions
Chapter 4: Recurrences
Chapter 5: Probabilistic Analysis and Randomized Algorithms

page: 109
Part II: Sorting and Order Statistics
Chapter 6: Heapsort
Chapter 7: Quicksort
Chapter 8: Sorting in Linear Time
Chapter 9: Medians and Order Statistics

page: 172
Part III: Data Structures
Chapter 10: Elementary Data Structures
10.1 Stacks and queues
10.2 Linked lists
10.3 Implementing pointers and objects
10.4 Representing rooted trees
Chapter 11: Hash Tables (page:192)
11.1 Direct-address tables
11.2 Hash tables
11.3 Hash functions
11.4 Open addressing
11.5 Perfect hashing
Chapter 12: Binary Search Trees(page:220)
12.1 What is a binary search tree?
12.2 Querying a binary search tree
12.3 Insertion and deletion
12.4 Randomly built binary search trees
Chapter 13: Red-Black Trees(page:238)
13.1 Properties of red-black trees
13.2 Rotations
13.3 Insertion
13.4 Deletion
Chapter 14: Augmenting Data Structures(page:261)
14.1 Dynamic order statistics
14.2 How to Augment a Data Structure
14.3 Interval Trees

page: 276
Part IV: Advanced Design and Analysis Techniques
Chapter 15: Dynamic Programming
Chapter 16: Greedy Algorithms
Chapter 17: Amortized Analysis

page: 369
Part V: Advanced Data Structures
Chapter 18: B-Trees
Chapter 19: Binomial Heaps
Chapter 20: Fibonacci Heaps
Chapter 21: Data Structures for Disjoint Sets

page: 444
Part VI: Graph Algorithms
Chapter 22: Elementary Graph Algorithms
Chapter 23: Minimum Spanning Trees
Chapter 24: Single-Source Shortest Paths
Chapter 25: All-Pairs Shortest Paths
Chapter 26: Maximum Flow

page: 598
Part VII: Selected Topics
Chapter 27: Sorting Networks
Chapter 28: Matrix Operations
Chapter 29: Linear Programming
Chapter 30: Polynomials and the FFT
Chapter 31: Number-Theoretic Algorithms
Chapter 32: String Matching
Chapter 33: Computational Geometry
Chapter 34: NP-Completeness
Chapter 35: Approximation Algorithms

page: 919
Part VIII: Appendix: Mathematical Background
Appendix A: Summations
Appendix B: Sets, Etc.
Appendix C: Counting and Probability