R10. Distributed Algorithms - Uedu Open

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R10. Distributed Algorithms

6.046J - Design and Analysis of Algorithms

其他影片 (34)

1 1. Course Overview, Interval Scheduling 2 2. Divide & Conquer: Convex Hull, Median Finding 3 R1. Matrix Multiplication and the Master Theorem 4 3. Divide & Conquer: FFT 5 R2. 2-3 Trees and B-Trees 6 4. Divide & Conquer: van Emde Boas Trees 7 5. Amortization: Amortized Analysis 8 6. Randomization: Matrix Multiply, Quicksort 9 R4. Randomized Select and Randomized Quicksort 10 7. Randomization: Skip Lists 11 8. Randomization: Universal & Perfect Hashing 12 R5. Dynamic Programming 13 9. Augmentation: Range Trees 14 10. Dynamic Programming: Advanced DP 15 11. Dynamic Programming: All-Pairs Shortest Paths 16 12. Greedy Algorithms: Minimum Spanning Tree 17 R6. Greedy Algorithms 18 13. Incremental Improvement: Max Flow, Min Cut 19 14. Incremental Improvement: Matching 20 R7. Network Flow and Matching 21 15. Linear Programming: LP, reductions, Simplex 22 16. Complexity: P, NP, NP-completeness, Reductions 23 R8. NP-Complete Problems 24 17. Complexity: Approximation Algorithms 25 18. Complexity: Fixed-Parameter Algorithms 26 R9. Approximation Algorithms: Traveling Salesman Problem 27 19. Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees 28 20. Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees 29 R10. Distributed Algorithms 30 21. Cryptography: Hash Functions 31 22. Cryptography: Encryption 32 R11. Cryptography: More Primitives 33 23. Cache-Oblivious Algorithms: Medians & Matrices 34 24. Cache-Oblivious Algorithms: Searching & Sorting

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Design and Analysis of Algorithms

課程影片 (34)

1 1. Course Overview, Interval Scheduling 2 2. Divide & Conquer: Convex Hull, Median Finding 3 R1. Matrix Multiplication and the Master Theorem 4 3. Divide & Conquer: FFT 5 R2. 2-3 Trees and B-Trees 6 4. Divide & Conquer: van Emde Boas Trees 7 5. Amortization: Amortized Analysis 8 6. Randomization: Matrix Multiply, Quicksort 9 R4. Randomized Select and Randomized Quicksort 10 7. Randomization: Skip Lists 11 8. Randomization: Universal & Perfect Hashing 12 R5. Dynamic Programming 13 9. Augmentation: Range Trees 14 10. Dynamic Programming: Advanced DP 15 11. Dynamic Programming: All-Pairs Shortest Paths 16 12. Greedy Algorithms: Minimum Spanning Tree 17 R6. Greedy Algorithms 18 13. Incremental Improvement: Max Flow, Min Cut 19 14. Incremental Improvement: Matching 20 R7. Network Flow and Matching 21 15. Linear Programming: LP, reductions, Simplex 22 16. Complexity: P, NP, NP-completeness, Reductions 23 R8. NP-Complete Problems 24 17. Complexity: Approximation Algorithms 25 18. Complexity: Fixed-Parameter Algorithms 26 R9. Approximation Algorithms: Traveling Salesman Problem 27 19. Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees 28 20. Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees 29 R10. Distributed Algorithms 30 21. Cryptography: Hash Functions 31 22. Cryptography: Encryption 32 R11. Cryptography: More Primitives 33 23. Cache-Oblivious Algorithms: Medians & Matrices 34 24. Cache-Oblivious Algorithms: Searching & Sorting