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Design and Analysis of Algorithms

Design and Analysis of Algorithms. Instructor: Prof. Abhiram Ranade, Department of Computer Science, IIT Bombay. This course covers lessons on divide and conquer, greedy algorithm, pattern matching, dynamic programming and approximation algorithm. The main goal of this course teaches you to design algorithms which are fast. In this course you will study well defined design techniques through lots of exercises. We hope that at the end of the course you will be able to solve algorithm design problems that you may encounter later in your life. (from nptel.ac.in)

Lecture 13 - Greedy Algorithms IV


Go to the Course Home or watch other lectures:

Lecture 01 - Overview
Lecture 02 - Framework for Algorithms Analysis
Lecture 03 - Framework for Algorithms Analysis (cont.)
Lecture 04 - Asymptotic Notations
Lecture 05 - Algorithm Design Techniques: Basics
Lecture 06 - Divide-and-Conquer
Lecture 07 - Divide-and-Conquer: Median Finding
Lecture 08 - Divide-and-Conquer: Surfing Lower Bounds
Lecture 09 - Divide-and-Conquer: Closest Pair
Lecture 10 - Greedy Algorithms I
Lecture 11 - Greedy Algorithms II
Lecture 12 - Greedy Algorithms III
Lecture 13 - Greedy Algorithms IV
Lecture 14 - Pattern Matching I
Lecture 15 - Pattern Matching II
Lecture 16 - Combinational Search and Optimization I
Lecture 17 - Combinational Search and Optimization II
Lecture 18 - Dynamic Programming
Lecture 19 - Longest Common Subsequences
Lecture 20 - Matrix Chain Multiplication
Lecture 21 - Scheduling with Startup and Holding Costs
Lecture 22 - Average Case Analysis of Quicksort
Lecture 23 - Bipartite Maximum Matching
Lecture 24 - Lower Bounds for Sorting
Lecture 25 - Element Distinctness Lower Bounds
Lecture 26 - NP-Completeness I
Lecture 27 - NP-Completeness II
Lecture 28 - NP-Completeness III
Lecture 29 - NP-Completeness IV
Lecture 30 - NP-Completeness V
Lecture 31 - NP-Completeness VI
Lecture 32 - Approximation Algorithms for NP-Complete Problems
Lecture 33 - Approximation Algorithms for NP-Complete Problems (cont.)
Lecture 34 - Approximation Algorithms for NP-Complete Problems (cont.)