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MIT 6.046J Design and Analysis of Algorithms, Spring 2015
2. Divide & Conquer: Convex Hull, Median Finding
24. Cache-Oblivious Algorithms: Searching & Sorting
7. Randomization: Skip Lists
R2. 2-3 Trees and B-Trees
14. Incremental Improvement: Matching
R10. Distributed Algorithms
15. Linear Programming: LP, reductions, Simplex
R6. Greedy Algorithms
1. Course Overview, Interval Scheduling
10. Dynamic Programming: Advanced DP
13. Incremental Improvement: Max Flow, Min Cut
4. Divide & Conquer: van Emde Boas Trees
21. Cryptography: Hash Functions
R9. Approximation Algorithms: Traveling Salesman Problem
12. Greedy Algorithms: Minimum Spanning Tree
3. Divide & Conquer: FFT
R11. Cryptography: More Primitives
22. Cryptography: Encryption
20. Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees
R7. Network Flow and Matching
R4. Randomized Select and Randomized Quicksort
6. Randomization: Matrix Multiply, Quicksort
9. Augmentation: Range Trees
8. Randomization: Universal & Perfect Hashing
R1. Matrix Multiplication and the Master Theorem
11. Dynamic Programming: All-Pairs Shortest Paths
R8. NP-Complete Problems
17. Complexity: Approximation Algorithms
19. Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees
R5. Dynamic Programming
5. Amortization: Amortized Analysis
18. Complexity: Fixed-Parameter Algorithms
16. Complexity: P, NP, NP-completeness, Reductions
23. Cache-Oblivious Algorithms: Medians & Matrices