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Lecture 28: Gusfield recaps NP-completeness.
The professor discusses coping with NP-complete problems: approximation algorithms and lowering the exponent of exponential-time algorithms.
The professor discusses coping with NP-complete problems: approximation algorithms and lowering the exponent of exponential-time algorithms.
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BUSCAR EPISODIOS ANTERIORES
Buscar episodios anteriores de Algorithm Design and Analysis.
OTROS EPISODIOS EN ESTE PODCAST
Lecture 27 covers the major theorems of NP-completeness, P = NP question, and how to prove a new problem in NP-complete.
Lecture 24 gives an introduction to P and NP and polynomial-time reductions.
Lecture 23 covers approximation algorithms - definition, factor of two approximation for the center cover problem.
In Lecture 26, Gusfield gives correct, formal definitions of P and NP, ending with a brief definition of NP-complete problems (languages).
Lecture 25 deals with an intuitive view of NP - not the correct formal definition.
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