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Quantifying efficiency: O( ), Omega( ), Theta( )
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Classroom Contents
Design and Analysis of Algorithms
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- 1 Course Outline
- 2 Example: Air Travel
- 3 Example: Xerox shop
- 4 Example: Document similarity
- 5 Introduction and motivation
- 6 Input size, worst case, average case
- 7 Quantifying efficiency: O( ), Omega( ), Theta( )
- 8 Examples: Analysis of iterative and recursive algorithms
- 9 Arrays and lists
- 10 Searching in an array
- 11 Selection Sort
- 12 Insertion sort
- 13 Merge sort
- 14 Merge sort - analysis
- 15 Quicksort
- 16 Quicksort - analysis
- 17 Sorting - Concluding remarks
- 18 Introduction to graphs
- 19 Representing graphs
- 20 Breadth first search (BFS)
- 21 Depth first search (DFS)
- 22 Applications of BFS and DFS
- 23 Directed acylic graphs: topological sort
- 24 Directed acylic graphs: longest paths
- 25 Dijkstras algorithm: analysis
- 26 Negative edge weights: Bellman-Ford algorithm
- 27 All pairs shortest paths
- 28 Minimum Cost Spanning Trees
- 29 Prims Algorithm
- 30 Kruskals algorithm
- 31 Union-Find using arrays
- 32 Union-Find using pointers
- 33 Priority queues
- 34 Heaps
- 35 Heaps: Updating values, sorting
- 36 Counting inversions
- 37 Closest pair of points
- 38 Binary Search Trees
- 39 Balanced search trees
- 40 Interval scheduling
- 41 Scheduling with deadlines: minimizing lateness
- 42 Huffman codes
- 43 Introduction to dynamic programming
- 44 Memoization
- 45 Grid paths
- 46 Common subwords and subsequences
- 47 Edit distance
- 48 Matrix multiplication
- 49 Linear Programming
- 50 LP modelling: Production Planning
- 51 LP modelling: Bandwidth allocation
- 52 Network Flows
- 53 Reductions
- 54 Checking Algorithms
- 55 P and NP
- 56 Single source shortest paths: Dijkstras algorithm
