Lecture Notes For All: Introduction To Algorithms Cormen

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Wednesday, February 24, 2010

Introduction To Algorithms Cormen

Introduction To Algorithms Cormen





Description:
This course will provide a rigorous introduction to the design and analysis of algorithms. We will discuss classic problems (e.g., sorting, traveling salesman problem), classic algorithm design strategies (e.g., divide-and-conquer, greedy approaches), and classic algorithms and data structures (e.g., hash tables, Dijkstra's algorithm). We will also analyze algorithm complexity throughout, and touch on issues of tractibility such as "NP-Completeness".



Lectures:

A tentative schedule of lecture topics is given below.
NumberTopicSourceText
1Introduction, administration, time and space complexity

PPT

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2Basics: asymptotic notationPPT3.1-3.2
3Basics: recurrences (mergesort)PPT4.1
4Basics: recurrences continued, master theoremPPT4.3, 6.1-6.2
5Sorting: intro to heapsortPPT6, 7.1-7.3
6Sorting: heapsort, priority queuesPPT7.4
7Sorting: quicksortPPT5.1-5.3
8Sorting: quicksort average case analysisPPT5.4 last section
9Sorting: linear time sorting algorithmsPPT8.1-8.2
10Sorting: linear time algorithms continued;

Order statistics: selection in expected linear time		PPT8.3-8.4

9.1-9.2
11Order statistics: selection in worst-case linear timePPT9.3
12Review for examPPT
13Structures: binary search treesPPT12.1-12.3
14Structures: red-black treesPPT13.1-13.2
15Structures: red-black trees (insertion)PPT13.3-13.4
16Structures: skip listsPPT--
17Structures: skip lists, hash tables PPT11.1-11.2
18Structures: hash tables (hash functions)PPT11.3-11.4
19Structures: hash tables (universal hashing)PPT11.3-11.4
20Augmenting structures: dynamic order statisticsPPT14.1-14.2
21Augmenting structures: interval treesPPT14.3
22Graph algorithms: the basicsPPT22.1-22.3
23Graph algorithms: BFSPPT22.3
24Graph algorithms: DFSPPT23.1
25Minimum spanning treesPPT23.2
26Shortest paths: Bellman-FordPPT24.1-24.3
27Shortest paths: DAG, Dijkstra's algorithmPPT
28Finish Dijkstra's. Kruskals algorithm; disjoint setsPPT21.1-21.3, 23.2
29Disjoint sets; amortized analysisPPT17.1-17.2
30Amortized analysis continuedPPT17.3-17.4
31Dynamic programmingPPT15.1, 15.3
32Dynamic programming (longest common subsequence)PPT15.4
33Dynamic programming (knapsack problem)PPT
34Greedy algorithms PPT16.1-16.2
35NP-CompletenessPPT34.1-34.2
36NP-Completeness continuedPPT34.1-34.2
37NP-Completeness: reductionsPPT34.3-4
38NP-Completeness: reductionsPPT34.3-4
39Review for finalPPT--
at 9:26 AM

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