MIT 6.046J Design and Analysis of Algorithms, Spring 2015
MIT 6.046J Design and Analysis of Algorithms, Spring 2015
View the complete course: http://ocw.mit.edu/6-046JS15
Instructor: Prof. Erik Demaine, Prof. Srini Devadas, Prof. Nancy Lynch
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1. Course Overview, Interval Scheduling
01:23:35
2. Divide & Conquer_ Convex Hull, Median Finding
01:20:35
3. Divide & Conquer_ FFT
01:20:52
4. Divide & Conquer_ van Emde Boas Trees
01:20:15
5. Amortization_ Amortized Analysis
01:15:53
6. Randomization_ Matrix Multiply, Quicksort
01:21:52
7. Randomization_ Skip Lists
01:20:56
8. Randomization_ Universal & Perfect Hashing
01:21:51
9. Augmentation_ Range Trees
01:24:34
10. Dynamic Programming_ Advanced DP
01:20:08
11. Dynamic Programming_ All-Pairs Shortest Paths
01:21:49
12. Greedy Algorithms_ Minimum Spanning Tree
01:22:10
13. Incremental Improvement_ Max Flow, Min Cut
01:22:58
14. Incremental Improvement_ Matching
01:22:33
15. Linear Programming_ LP, reductions, Simplex
01:22:27
16. Complexity_ P, NP, NP-completeness, Reductions
01:25:25
17. Complexity_ Approximation Algorithms
01:21:08
18. Complexity_ Fixed-Parameter Algorithms
01:17:43
19. Synchronous Distributed Algorithms_ Symmetry-Breaking. Shortest-Paths Spanni
01:17:34
20. Asynchronous Distributed Algorithms_ Shortest-Paths Spanning Trees
01:12:03
21. Cryptography_ Hash Functions
01:22:01
22. Cryptography_ Encryption
01:24:15
23. Cache-Oblivious Algorithms_ Medians & Matrices
01:20:28
24. Cache-Oblivious Algorithms_ Searching & Sorting
01:17:41
R1. Matrix Multiplication and the Master Theorem
53:46
R2. 2-3 Trees and B-Trees
30:45
R4. Randomized Select and Randomized Quicksort
39:30
R5. Dynamic Programming
52:03
R6. Greedy Algorithms
22:24
R7. Network Flow and Matching
51:12
R8. NP-Complete Problems
45:47
R9. Approximation Algorithms_ Traveling Salesman Problem
31:59
R10. Distributed Algorithms
50:19
R11. Cryptography_ More Primitives
49:30
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