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yqian1 发表于 2008-7-1 00:03

求算法书

上次小弟求一本离散数学,一位大侠介绍了The Discrete Mathematics And Its Applications,这本书真的不错,由于是英文原版,顺便可以加强一下计算机方面的专业英语术语。
kJe-U;jn$jo4p        现在请大侠们推荐一本有关算法的书,基础的,不要太精深。
eh1xKZL$CV*p        小弟不胜感激。

chavanel 发表于 2008-7-1 00:27

唯有MIT的Introduction to Algorithms最经典 mQB X?n
高深的有the art of computer programming好像是volume II是讲算法的

Bill_Ma 发表于 2008-7-3 10:04

先看mit的Introduction to Algorithms吧,这本比较全但是深度不太够"Lo(y&v? ~L3O oa&L
然后可以看下cornell的Algorithm Design,这本是近几年新出的难得一见的好书,姚期智重点推荐的算法教材。本科生这两本足够了
+G({DBdL!t;m 有余力的话,可以看下knuth的TAOCP的1、3卷,第2卷是讲半数值算法的
;Rj_2bQL|V 你要是侧重算法实现的话,推荐knuth的弟子Robert Sedgewick写的书Algorithms in C或者Algorithms in C++

ssanic 发表于 2008-7-16 11:06

基础的就看上面说的那本Introduction to Algorithms吧,国内的翻译叫“算法导论”,绿皮的,比较厚

x_lee 发表于 2008-7-16 16:18

基础的我觉得国内的数据结构那本也还不错啊, 只是不很全.
!ZzB+ApD V Knuth的书好难的.....

zmoqingsong 发表于 2008-7-17 14:07

[quote]原帖由 [i]Bill_Ma[/i] 于 2008-7-3 10:04 发表 [url=http://bbs.taisha.org/redirect.php?goto=findpost&pid=12026032&ptid=1079518][img]http://bbs.taisha.org/images/common/back.gif[/img][/url]k{$G*Vk8A
先看mit的Introduction to Algorithms吧,这本比较全但是深度不太够
i3rd!Y'|m:uk 然后可以看下cornell的Algorithm Design,这本是近几年新出的难得一见的好书,姚期智重点推荐的算法教材。本科生这两本足够了
?A@ \2RKf&Cg)_5l 有余力的话,可以 ... [/quote]
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a2c { Nbb ? \O/u%I%a(EY
Algorithm Design
#Ut hI7I9e^
t}ac S,o.o
l1F G\Y2t_v\'o Table of Contents
&hF#BX @*Y5I.X|*L
&lM}s*J"t(w2KT [img=495,1]http://www.aw-bc.com/info/kleinberg/assets/images/rule.gif[/img]
1l5]%]-Pt7}cI-~{
h]w?"Z8H2Q/{ [b]Preface[/b]
3v7@3jr$W4y;e2HC [b]Chapter 1: Introduction: [i]Some Representative Problems[/i][/b]
V9E1L Q7QH[bSW 1.1 A First Problem: Stable Matching nRRiWMbe
1.2 Five Representative Problems c}JpC(|
1.3 Solved Exercises1T0@a'l:s MJ
1.4 Excercises
^)T!oa"d2v 1.5 Notes and Further Reading
iTN de9t
|C Xg j-Nx'd [b]Chapter 2: Basics of Algorithms Analysis[/b]
b+ez/O n|v'a 2.1 Computational Tractability
F,p'mD@ Dx YaB 2.2 Asymptotic Order of Growth NotationB[Co q@G/Pf
2.3 Implementing the Stable Matching Algorithm using Lists and Arrays
K,[N9K0\r;Y 2.4 A Survey of Common Running Timesg)Zt,V RLN
2.5 A More Complex Data Structure: Priority Queues
3g!EMgyWV 2.6 Solved Exercises
:e] Rro 2.5 Exercises
v(Vi&orY't5^8b 2.7 Notes and Further Reading
#vsoD w9A
xaM X'hY1g{ [b]Chapter 3: Graphs[/b]!Sv2h$~)Q9x xZ:]!n)TH
3.1 Basic Definitions and Applications!c3q$N.J z
3.2 Graph Connectivity and Graph TraversalW-In,i2g
3.3 Implementing Graph Traversal using Queues and Stacks(@0Uk"`-CV'BXH6y
3.4 Testing Bipartiteness: An Application of Breadth-First Search
4w-~HI1{A,P/MPl 3.5 Connectivity in Directed Graphs [D[1a3k-I7e.c
3.6 Directed Acyclic Graphs and Topological Ordering
X!R6n`9KR y v 3.7 Solved Exercises
| UK A){9w~dg0D 3.8 ExercisesR&TS'X/a|,B X3a
3.9 Notes and Further ReadingP#Aw%sb3i:r
!Co'GB"s.uU
[b]Chapter 4: Greedy Algorithms[/b]-T0\Zk)}HH
4.1 Interval Scheduling: The Greedy Algorithm Stays Ahead
n"s3B8N9}i)}+g 4.2 Scheduling to Minimize Lateness: An Exchange Argumentt&@.m DWs7|(H
4.3 Optimal Caching: A More Complex Exchange Argument
8D]a9A#F"RPCn} 4.4 Shortest Paths in a GraphJdN2n,P
4.5 The Minimum Spanning Tree Problem D aMF5G2K4l
4.6 Implementing Kruskal's Algorithm: The Union-Find Data Structure
'k AQs%Yfu 4.7 Clustering
gsX-y wq2@| 4.8 Huffman Codes and the Problem of Data Compression
m$pj4i-f 4.9 (*) Minimum-Cost Arborescences: A Multi-Phase Greedy Algorithm
K;Xz-K#f#iDZ#|O"Y 4.10 Solved Exercises
4|e|Bp Pl 4.11 Excercises:`_9W1v8jr"N
4.12 Notes and Further Reading
FkN3^(?[\
%Tp{Gi? [b]Chapter 5: Divide and Conquer[/b]m.]A,f/P0?
5.1 A First Recurrence: The Mergesort AlgorithmQ Z,z J A%[_tl
5.2 Further Recurrence Relations6@s*bN ]k'p
5.3 Counting Inversions _Ib&l1o9xA
5.4 Finding the Closest Pair of Points
(Zu ?(Gf1E"S 5.5 Integer Multiplication
#W!~_"f&{W5|"[G 5.6 Convolutions and The Fast Fourier Transform_7d6e3d*y d
5.7 Solved Exercises
1B9JE}&EZ 5.8 ExercisesJ$Pi'y0\ t,P
5.9 Notes and Further Reading [url=http://www.aw-bc.com/info/kleinberg/toc.html#TOP][img=24,24]http://www.aw-bc.com/info/kleinberg/assets/images/icons/download.gif[/img][/url]
8P(M9km2gD,B2L [b]Chapter 6: Dynamic Programming[/b] ES)s U\ r&P9pB A;s
6.1 Weighted Interval Scheduling: A Recursive Procedure
9mrKqJ){{1B 6.2 Weighted Interval Scheduling: Iterating over Sub-Problems
j:m+[(aj:Z]r 6.3 Segmented Least Squares: Multi-way Choices
[2C%w6n]-tJC 6.4 Subset Sums and Knapsacks: Adding a Variable
0Zs%X i/mio3g8P 6.5 RNA Secondary Structure: Dynamic Programming Over Intervals:{z JD-xwx
6.6 Sequence Alignment:g"I/Dn:z,I \V
6.7 Sequence Alignment in Linear Space
jL!L5~t)w/e 6.8 Shortest Paths in a Graph'y[Ed?'@4Z
6.9 Shortest Paths and Distance Vector Protocols
b%Wx9|4}9V#PTO,N]0Zk 6.10 (*) Negative Cycles in a Graph K6{Pa8VR
6.11 Solved Exercises bKb$VgF7M
6.12 Exercises+| cf,j:[qt
6.13 Notes and Further Reading
a J)Z"G!hi8P
#n1rXD;G [b]Chapter 7: Network Flow[/b]
V[X+]G:r 7.1 The Maximum Flow Problem and the Ford-Fulkerson Algorithm
s iMff"u7Q.T 7.2 Maximum Flows and Minimum Cuts in a Network
r`)}TF 7.3 Choosing Good Augmenting Paths
y{%f @,o EIq7M$Gyy 7.4 (*) The Preflow-Push Maximum Flow AlgorithmjIbzee
7.5 A First Application: The Bipartite Matching Problem"W\"w&c z2cl-cH[
7.6 Disjoint Paths in Directed and Undirected Graphsk9|I`T0}_ ~
7.7 Extensions to the Maximum Flow Problem
6|:o;i^N0T$`Y 7.8 Survey Design
/\*J xCjuK7Q 7.9 Airline Schedulingu*s)D)\:qL |y2^'N
7.10 Image Segmentationt U*g%j9S
7.11 Project Selection
+w,RRcry 7.12 Baseball Elimination
:S@8e#_S(R_7q 7.13 (*) A Further Direction: Adding Costs to the Matching Problem t)j#o/wK Vsp?
7.14 Solved Exercisesf-lX/S o@5Z
7.15 Exercises%G\;b`0T-hz1W?7`q
7.16 Notes and Further Reading
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;HC6i:T/}z*q [b]Chapter 8: NP and Computational Intractability[/b]
;Y*X_2@F#q 8.1 Polynomial-time Reductions
XtH n_ 8.2 Efficient Certification and the Definition of NP%C ] ~BN\.`q
8.3 NP-Complete Problems ~p(L"Ie8il C
8.4 Sequencing Problems
l N3Y6{Y/p&T 8.5 Partitioning Problemso5s5bO8]
8.6 Graph Coloring
j0h7@F't8Y 8.7 Numerical Problems
&q&}1gb;J8J3Q,R)z%Y2_ 8.8 co-NP and the Asymmetry of NP
7u5c;XV j;E? Q8Q 8.9 A Partial Taxonomy of Hard Problemsk;S WNV7Q
8.10 Solved ExercisesZ/^ jIE;~
8.11 Exercises [E8q F`*oIwtLRN
8.12 Notes and Further Readingb`6?z6^j-r
0N2x+KO1n;SMl
[b]Chapter 9: PSPACE: [i]A Class of Problems Beyond NP[/i][/b]H n f*T_
9.1 PSPACEWO|h0N"KU$^7b
9.2 Some Hard Problems in PSPACE
} [#f8qL 9.3 Solving Quantified Problems and Games in Polynomial Space
+]-w"?5B#mX 9.4 Solving the Planning Problem in Polynomial Space8O-\H0UL[V+Mxf[
9.5 Proving Problems PSPACE-CompleteR/MG5XI1g.L
9.6 Solved Exercises
$U ]5R#S3u!{&ly0U2P0@ 9.7 Exercises
"Z_(tu8w5q 9.8 For Further Reading
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)U:DP0q:R} [b]Chapter 10: Extending the Limits of Tractability[/b]
aM0oV1ST*]"M 10.1 Finding Small Vertex Covers
|U#nm qN;u 10.2 Solving NP-hard Problem on Treese#i dw{MN @
10.3 Coloring a Set of Circular Arcs
Mm(]7p6F 10.4 (*) Tree Decompositions of Graphsdf$V)CDRs
10.5 (*) Constructing a Tree Decomposition| E+i HIn"v
10.6 Solved Exercises
i:w3PHFf5jh-@3F 10.7 Exercises
0pP5L B!X7uk+`PAk 10.8 Notes and Further Reading [url=http://www.aw-bc.com/info/kleinberg/toc.html#TOP][img=24,24]http://www.aw-bc.com/info/kleinberg/assets/images/icons/download.gif[/img][/url]
^9PyQ5G [b]Chapter 11: Approximation Algorithms[/b]%Q3pg!t2[%S
11.1 Greedy Algorithms and Bounds on the Optimum: A Load Balancing Problem
N0Am}hP 11.2 The Center Selection Problemwf ? d@#?y
11.3 Set Cover: A General Greedy Heuristic
!l}VR U 11.4 The Pricing Method: Vertex Cover mq4o(_Z
11.5 Maximization via the Pricing method: The Disjoint Paths Problem#d&CU~ Cfy
11.6 Linear Programming and Rounding: An Application to Vertex Cover/Apr1L]b!p
11.7 (*) Load Balancing Revisited: A More Advanced LP Application
2B3]+s+A4PM"M'r3z"\LN 11.8 Arbitrarily Good Approximations: the Knapsack Problem
F$x8{ p8y4X5j\;w 11.9 Solved Exercises
|I/Ae @ 11.10 Exercises
L&_QCsS 11.11 Notes and Further Reading Zz%a?!O+w{1e!r
nG4H3IE? n
[b]Chapter 12: Local Search[/b]
gH6k!i$z 12.1 The Landscape of an Optimization Problem*O+A({4a9ds!l
12.2 The Metropolis Algorithm and Simulated Annealing {%|3aPCic dD
12.3 An Application of Local Search to Hopfield Neural Networks$f+E d4zc%y
12.4 Maximum Cut Approximation via Local Search#X;e.n?/L(X'\qG
12.5 Choosing a Neighbor Relation1J,{8Q;}&X X0[B
12.6 (*) Classification via Local Search5vH2gM r7|Z
12.7 Best-Response Dynamics and Nash Equilibria'I4Dd$O J L
12.8 Solved Exercises
YvtFe1L J 12.9 Exercises
|+xv1FP+C x 12.10 Notes and Further Reading
aIeMk)^(zo 4\.W s\3vo dE
[b]Chapter 13: Randomized Algorithms[/b]
Z{8T%[,X P~{ 13.1 A First Application: Contention Resolutioni \;o&d?
13.2 Finding the Global Minimum CutY(u+J}:Xqi5E
13.3 Random Variables and their Expectations
B)EsFUV 13.4 A Randomized Approximation Algorithm for MAX-3-SAT
^,RORP 13.5 Randomized Divide-and-Conquer: Median-Finding and Quicksort!g2a$f]e"uI
13.6 Hashing: A Randomized Implementation of Dictionaries
-y4A!~1f4C1n3nh D+q 13.7 Finding the Closest Pair of Points: A Randomized Approach
rHdDW g-Zg u 13.8 Randomized Caching
@ Z_E$g f^.fY 13.9 Chernoff Bounds
5KK f$F8}M 13.10 Load Balancing
|vjT%{%] @5R@P} 13.11 (*) Packet RoutingS]H;Mi,S\#b+e
13.12 Background: Some Basic Probability Definitions
2WC-N D jc"r7Bs U 13.13 Solved Exercises
J-@*S GY;n$E*z"T 13.14 Exercisesa @;M-p |({,Fu
13.15 Notes and Further ReadingiTi;d G:v5m
Ln\/ldy8S4B
[b]Epilogue: Algorithms that Run Forever[/b] [url=http://www.aw-bc.com/info/kleinberg/toc.html#TOP][img=24,24]http://www.aw-bc.com/info/kleinberg/assets/images/icons/download.gif[/img][/url]

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