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Lecture - 17 Combinational Search and Optimization II
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Classroom Contents
Design and Analysis of Algorithms
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- 1 Lecture - 1 Overview of the course
- 2 Lecture - 2 Framework for Algorithms Analysis
- 3 Lecture - 3 Algorithms Analysis Framework - II
- 4 Lecture - 4 Asymptotic Notation
- 5 Lecture -5 Algorithm Design Techniques : Basics
- 6 Lecture -6 Divide And Conquer-I
- 7 Lecture -7 Divide And Conquer -II Median Finding
- 8 Lecture -8 Divide And Conquer -III Surfing Lower Bounds
- 9 Lecture -9 Divide And Conquer -IV Closest Pair
- 10 Lecture -10 Greedy Algorithms -I
- 11 Lecture - 11 Greedy Algorithms - II
- 12 Lecture - 12 Greedy Algorithms - III
- 13 Lecture - 13 Greedy Algorithms - IV
- 14 Lecture - 14 Pattern Matching - I
- 15 Lecture - 15 Pattern Matching - II
- 16 Lecture -16 Combinational Search and Optimization I
- 17 Lecture - 17 Combinational Search and Optimization II
- 18 Lecture -18 Dynamic Programming
- 19 Lecture 19 Longest Common Subsequences
- 20 Lecture -20 Matric Chain Multiplication
- 21 Lecture - 21 Scheduling with Startup and Holding Costs
- 22 Lecture - 22 Average case Analysis of Quicksort
- 23 Lecture - 23 Bipartite Maximum Matching
- 24 Lecture - 24 Lower Bounds for Sorting
- 25 Lecture -25 Element Distinctness Lower Bounds
- 26 Lecture -26 NP-Completeness-I -Motivation
- 27 Lecture - 27 NP - Compliteness - II
- 28 Lecture - 28 NP-Completeness - III
- 29 Lecture - 29 NP-Completeness - IV
- 30 Lecture - 30 NP-Completeness - V
- 31 Lecture - 31 NP-Completeness - VI
- 32 Lecture - 32 Approximation Algorithms
- 33 Lecture - 33 Approximation Algorithms
- 34 Lecture - 34 Approximation Algorithms for NP
