Wednesday, 5 November 2014

Design of Algorithms

Algorithms

Number Date Topic Source Text
1 1/16 Introduction, administration, time and space complexity --
2 1/18 Basics: asymptotic notation PPT 3.1-3.2
3 1/21 Basics: recurrences (mergesort) PPT 4.1
4 1/23 Basics: recurrences continued, master theorem PPT 4.3, 6.1-6.2
5 1/25 Sorting: intro to heapsort PPT 6, 7.1-7.3
6 1/28 Sorting: heapsort, priority queues PPT 7.4
7 1/30 Sorting: quicksort PPT 5.1-5.3
8 2/1 Sorting: quicksort average case analysis PPT 5.4 last section
9 2/4 Sorting: linear time sorting algorithms PPT 8.1-8.2
10 2/6 Sorting: linear time algorithms continued;
Order statistics: selection in expected linear time
PPT 8.3-8.4
9.1-9.2
11 2/8 Order statistics: selection in worst-case linear time PPT 9.3
12 2/11 Review for exam PPT
EXAM 2/13 EXAM 1: Basics, Sorting, Order Statistics
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13 2/15 Structures: binary search trees PPT 12.1-12.3
14 2/18 Structures: red-black trees PPT 13.1-13.2
15 2/20 Structures: red-black trees (insertion) PPT 13.3-13.4
16 2/22 Structures: skip lists PPT --
17 2/25 Structures: skip lists, hash tables  PPT 11.1-11.2
18 2/27 Structures: hash tables (hash functions) PPT 11.3-11.4
19 3/1 Structures: hash tables (universal hashing) PPT 11.3-11.4
20 3/4 Augmenting structures: dynamic order statistics PPT 14.1-14.2
21 3/6 Augmenting structures: interval trees PPT 14.3
22 3/8 Graph algorithms: the basics PPT 22.1-22.3
-- -- SPRING BREAK
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23 3/18 Graph algorithms: BFS PPT 22.3
24 3/20 Graph algorithms: DFS PPT 23.1
EXAM 3/22 EXAM 2: Data structures
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-- 3/25 Go over exam
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25 3/27 Minimum spanning trees PPT 23.2
26 3/29 Shortest paths: Bellman-Ford PPT 24.1-24.3
27 4/1 Shortest paths: DAG, Dijkstra's algorithm PPT
28 4/3 Finish Dijkstra's.  Kruskals algorithm; disjoint sets PPT 21.1-21.3, 23.2
29 4/5 Disjoint sets; amortized analysis PPT 17.1-17.2
30 4/8 Amortized analysis continued PPT 17.3-17.4
31 4/10 Dynamic programming  PPT 15.1, 15.3
32 4/12 Dynamic programming (longest common subsequence) PPT 15.4
33 4/15 Dynamic programming (knapsack problem) PPT
34 4/17 Greedy algorithms  PPT 16.1-16.2
35 4/19 NP-Completeness PPT 34.1-34.2
36 4/22 NP-Completeness continued PPT 34.1-34.2
37 4/24 NP-Completeness: reductions PPT 34.3-4
38 4/26 NP-Completeness: reductions PPT 34.3-4

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