LEJ4Learning
  1. Introduction
  2. Model of computation, 2-d maxima
  3. Analysis of 2-d Maxima
  4. Runtime analysis
  5. 2-d maxima: sweep line algorithm
  6. Asymptotic Notation
  7. Asymptotic notation, merge sort
  8. Analysis of Merge Sort
  9. Solving recurrence relations, median selection
  10. Median selection – partitioning algorithm
  11. Analysis of median selection, binary heaps, sorting
  12. Heap sort, analysis of heap sort
  13. Quick sort
  14. Analysis of quick sort
  15. Lower bounds for sorting, Linear time sorting, counting sort
  16. Bucket sort, radix sort, dynamic programming, Fibonacci sequence
  17. Dynamic programming – edit distance
  18. Dynamic programming – edit distance algorithm
  19. Dynamic programming – chain matrix multiply
  20. Dynamic programming – chain matrix multiply
  21. Dynamic programming – 0/1 knapsack
  22. Dynamic programming – 0/1 knapsack
  23. Greedy algorithms – coin change problem
  24. Greedy algorithms – Huffman encoding
  25. Greedy algorithms – Huffman encoding
  26. Greedy algorithms – Activity scheduling
  27. Greedy algorithms – fracitional knapsack, Graphs – definitions
  28. Graphs – representations, traversal
  29. Graphs – breadth-first search, generic traversal algorithms
  30. Graphs – generic traversal algorithms
  31. Graphs – depth-first search, timestamp structure
  32. Graphs – cycles, topological sorting
  33. Graphs – strong components
  34. Graphs – strong components, minimum spanning tree (MST)
  35. Graphs – MST: generic approach
  36. Graphs – MST: Kruskal’s algorithm
  37. Graphs – MST: Prim’s algorithm
  38. Graphs – shortest paths
  39. Graphs – Dijkstra’s algorithm
  40. Graphs – Dijkstra’s algorithm, Bellman-Ford algorithm
  41. Graphs – all-pairs shortest path, Floyd-Warshall’s algorithm
  42. Graphs – Floyd-Warshall algorithm
  43. Complexity theory -classes P, NP
  44. Complexity theory – Reductions, graph coloring
  45. Complexity theory – boolean satisfiability, independent sets

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