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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: Applications
Lecture 5: Weighted Matching
Lecture 6: Reductions and NP
Lecture 7: NP-Completeness
Lecture 8: TSP: Approximation and Inapproximability
Lecture 9: LP and Approximation
Lecture 10: Backward Analysis and LP. Convex hulls.
Lecture 11: Orthogonal range searching: kd-trees, range trees.
Lecture 12: Divide and conquer Algorithms
Lecture 13: Randomized algorithms.
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