Computer Algorithms - 2

Instructor: Prof. Dr. Shashank K. Mehta, Department of Computer Science and Engineering, IIT Kanpur.

The course discusses efficient algorithms from a large number of domains. This course assumes the knowledge of data structures, the knowledge big-O notation and the concept of time and space complexity of an algorithm. And also it will not introduce divide and conquer, dynamic programming, and greedy paradigms. This course will discuss graph algorithms, network-flow algorithms, geometric algorithms, string matching, matrix algorithms, polynomial computation algorithms, and number-theoretic algorithms.

Mod-01 Lec-01 Graph_Basics.
Mod-01 Lec-02 Breadth_First_Search.
Mod-01 Lec-03 Dijkstra_Algo.
Mod-01 Lec-04 All Pair Shortest Path.
Mod-01 Lec-05 Matriods.
Mod-01 Lec-06 Minimum Spanning Tree.
Mod-01 Lec-07 Edmond\\\'s Matching Algo I.
Mod-01 Lec-08 Edmond\'s Matching Algo II.
Mod-01 Lec-09 Flow Networks.
Mod-01 Lec-10 Ford Fulkerson Method.
Mod-01 Lec-11 Edmond Karp Algo.
Mod-01 Lec-12 Matrix Inversion.
Mod-01 Lec-13 Matrix Decomposition.
Mod-01 Lec-14 Knuth Morris Pratt Algo.
Mod-01 Lec-15 Rabin Karp Algo.
Mod-01 Lec-16 NFA Simulation.
mod-01 Lec-17 Integer-Polynomial Ops I.
Mod-01 Lec-18 Integer-Polynomial Ops II.
Mod-01 Lec-19 Integer-Polynomial OpsIII.
Mod-01 Lec-20 Chinese Remainder I.
Mod-01 Lec-21 Chinese Remainder II.
Mod-01 Lec-22 Chinese Remainder III.
Mod-01 Lec-23 Discrete Fourier Transform I.
Mod-01 Lec-24 Discrete Fourier Transform II.
Mod-01 Lec-25 Discrete Fourier Transform III.
Mod-01 Lec-26 Schonhage Strassen Algo.
Mod-01 Lec-27 Linear Programming I.
Mod-01 Lec-28 Linear Programming II.
Mod-01 Lec-29 Geometry I.
Mod-01 Lec-30 Geometry II.
Mod-01 Lec-31 Geometry III.
Mod-01 Lec-32 Approximation Algo I.
Mod-01 Lec-33 Approximation Algo II.
Mod-01 Lec-34 Approximation Algo III.
Mod-01 Lec-35 General: Dynamic Programming.