0.1 Books and algorithm
0.2 Enter Fibonacc
0.3 Big-O notatio15
Exercise
1 Algorithms with numbers 21
1.1 Basic arithmeti
1.2 Modular arithmeti
1.3 Primality testin
1.4 Cryptograph39
1.5 Universal hashin
Exercise . . 48
Randomized algorithms: a virtual chapter 39
2 Divide-and-conquer algorithms 55
2.1 Multiplicatio55
2.2 Recurrence relation
2.3 Mergesor0
2.4 Median
2.5 Matrix multiplicatio
2.6 The fast Fourier transfor
Exercise
3 Decompositions of graphs 91
3.1 Why graphs
3.2 Depth-first search in undirected graph
3.3 Depth-first search in directed graph
3.4 Strongly connected component
Exercise
4 Paths in graphs 115
4.1 Distance15
4.2 Breadth-first searc
4.3 Lengths on edge
4.4 Dijkstra’s algorith
4.5 Priority queue implementation
4.6 Shortest paths in the presence of negative edge
4.7 Shortest paths in dag
Exercise
5 Greedy algorithms 139
5.1 Minimum spanning tree
5.2 Huffman encodin
5.3 Horn formula
5.4 Set cover
Exercise
6 Dynamic programming 169
6.1 Shortest paths in dags, revisite
6.2 Longest increasing subsequence
6.3 Edit distanc
6.4 Knapsac
6.5 Chain matrix multiplicatio
6.6 Shortest path
6.7 Independent sets in tree
Exercise
7 Linear programming and reductions 201
7.1 An introduction to linear programmin
7.2 Flows in network
7.3 Bipartite matchin
7.4 Dualit
7.5 Zero-sum game
7.6 The simplex algorith
7.7 Postscript: circuit evaluatio
Exercise
8 NP-complete problems 247
8.1 Search problem
8.2 NP-complete problem
8.3 The reduction262 Exercise
9 Coping with NP-completeness 283
9.1 Intelligent exhaustive searc
9.2 Approximation algorithm
9.3 Local search heuristic
Exercise
10 Quantum algorithms 311
10.1 Qubits, superposition, and measuremen
10.2 The plan
10.3 The quantum Fourier transfor
10.4 Periodicit
10.5 Quantum circuit
10.6 Factoring as periodicit
10.7 The quantum algorithm for factorin
Exercise
Historical notes and further reading 331
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具體描述
This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest. Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal.
用戶評價
##就算不是程序員也非常值得讀一讀這本書 前麵兩章
評分##(http://www.cs.berkeley.edu/~vazirani/algorithms.html)果然彆具一格，不過量子算法沒看懂，很多練習都還需要想清楚——半吊子最可怕瞭，繼續學習。
評分##(http://www.cs.berkeley.edu/~vazirani/algorithms.html)果然彆具一格，不過量子算法沒看懂，很多練習都還需要想清楚——半吊子最可怕瞭，繼續學習。
評分##用過的算法教材，比導論更適閤當本科教材，可惜量子的部分我沒懂
評分##哈哈！！ http://beust.com/algorithms.pdf
評分##哈哈！！ http://beust.com/algorithms.pdf
評分我是看免費的 draft pdf http://www.cs.berkeley.edu/~vazirani/algorithms.html 相比CLRS，這本書採用不同的手法，耳目一新。
評分##終於讀完瞭。因為TA一本基礎算法課的原因，得經常翻這本書的一些章節（這本書是教材），覺得很不錯，在TA完瞭以後，希望可以係統得看完，隻能用零散的時間，所以看瞭很久。講到對它的評價，假設我這3年算法能力沒有什麼重大提高的話，這本書在對算法的分析和主綫的總結上，非常明顯的好於《算法導論》。
評分##讓你明白算法的現實背景和嚴謹數學證明。引導你結閤現實問題看算法
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