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Lecture 13 : Heap
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Introduction to Algorithms and Analysis
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- 1 Lecture 1 : Insertion sort
- 2 Lecture 2 : Analysis of Insertion Sort
- 3 Lecture 3 : Asymptotic Analysis
- 4 Lecture 4 : Recurrence of Merge Sort
- 5 Lecture 5 : Substitution Method
- 6 Lecture 6 : The Master Method
- 7 Lecture 7 : Divide-and-Conquer
- 8 Lecture 8 : Divide-and-Conquer (Contd.)
- 9 Lecture 9 : Straseen's Algorithms
- 10 Lecture 10 : QuickSort
- 11 Lecture 11 : Analysis of Quicksort.
- 12 Lecture 12 : Randomized Quicksort
- 13 Lecture 13 : Heap
- 14 Lecture 14 : Heap Sort
- 15 Lecture 15 : Decision Tree
- 16 Lecture 16 : Linear time Sorting
- 17 Lecture 17 : Radix Sort & Bucket Sort
- 18 Lecture 18 : Order Statistics
- 19 Lecture 19 : Randomised Order Statistics
- 20 Lecture 20 : Worst case linear time order statistics
- 21 Lecture 21 : Hash Function
- 22 Lecture 22 : Open Addressing
- 23 Lecture 23 : Universal Hashing
- 24 Lecture 24 : Perfect Hashing
- 25 Lecture 25 : Binary Search Tree (BST) Sort
- 26 Lecture 26 : Randomly build BST
- 27 Lecture 27 : Red Black Tree
- 28 Lecture 28 : Red Black Tree (Contd.)
- 29 Lecture 29 : Augmentation of data structure
- 30 Lecture 30 : Interval trees
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- 35 mod07lec35
- 36 Lecture 36 : Dynamic Programming
- 37 Lecture 37 : Longest common subsequence
- 38 Lecture 38 : Graphs
- 39 Lecture 39 : Prim's Algorithms
- 40 Lecture 40 : Graph Search
- 41 Lecture 41
- 42 Lecture 42
- 43 Lecture 43
- 44 Lecture 44
- 45 Lecture 45
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