Media Summary: Beating brute-force search for NP-hard problems. Fixed-parameter tractability: vertex cover revisited. Exact TSP via dynamic ... Introduction to linear programming. Geometric intuition. Applications: maximum and minimum-cost flow; linear regression; ... Proof of the max-flow/min-cut theorem. Augmenting on shortest paths (Edmonds-Karp). The blocking flow approach (Dinic).
A Second Course In Algorithms - Detailed Analysis & Overview
Beating brute-force search for NP-hard problems. Fixed-parameter tractability: vertex cover revisited. Exact TSP via dynamic ... Introduction to linear programming. Geometric intuition. Applications: maximum and minimum-cost flow; linear regression; ... Proof of the max-flow/min-cut theorem. Augmenting on shortest paths (Edmonds-Karp). The blocking flow approach (Dinic). Applications of multiplicative weights. Linear classifiers revisted. Minimax revisited (again). Applications to fast approximate flows. Online decision-making. Regret. The multiplicative weights Maximum flow: the push-relabel approach. Full
Five essential tools for the analysis of randomized
