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Lecture notes/slides will be posted here after class
(Beware: Some lecture slides will not be available online. I will note that in class before I teach
so that you can take notes if you want).
Lecture 1: Introduction (Stable Marriage) [demo]
Lecture 2: Max-Flow Min-Cut [demo]
Lecture 3: PreFlow Push [demo]
Lecture 4: MaxFlow MinCut: Applications
Lecture 5: Minimum weight perfect Matching
Lecture 6: Reductions and NP
Lecture 7: NP-Completeness
Lecture 8: TSP:Approximation and Inapproximability
Lecture 9: LP
Lecture 10: Halfspace Intersection and LP using RIC
Lecture 11: Convex Hulls and Range Searching
Lecture 12: kd-trees and k-clustering using MST
Lecture 13: Data Compression
Lecture 14: D&C [ Inversion Demo ]
Lecture 15: String Searching/Matching
Lecture 16: Online Algorithms
Lecture 17: Parallel Algorithms
Lecture 18: Guest Lecture on Network Algorithms by Dr. Aggarwal.
Lecture 19: Introduction to Machine Learning:
Perceptrons
Lecture 20: Review
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