Advanced Algorithms Lecture 16 Information Guide

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Lecture 16 | Programming Abstractions (Stanford)
Lecture 16 | Programming Abstractions (Stanford)
16. Complexity: P, NP, NP-completeness, Reductions
16. Complexity: P, NP, NP-completeness, Reductions
Lecture 16: Dijkstra
Lecture 16: Dijkstra
17. Complexity: Approximation Algorithms
17. Complexity: Approximation Algorithms
16. Strings
16. Strings
Advanced Algorithms - Fall 2018 - Lecture 16
Advanced Algorithms - Fall 2018 - Lecture 16

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Last Updated: October 1, 2026

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Summary

Simplex wrap-up, strong duality, complementary slackness, ellipsoid, intro to interior point. Power of random signs: ℓ2 norm estimation, subspace embeddings (regression), Johnson-Lindenstrauss, deterministic point ... MIT 6.046J Design and Analysis of Estimation so this is another very canonical application of randomized

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