Chapter: Introduction to randomized algorithms

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Home > Lectures on Proof Verification and Approximation Algorithms > Introduction to randomized algorithms

Lectures on Proof Verification and Approximation Algorithms |

Ernst W. Mayr; Hans Jürgen Prömel; Angelika Steger

Springer Berlin Heidelberg

Lectures on Proof Verification and Approximation Algorithms

Introduction to randomized algorithms

Chapter Info

Authors

Artur Andrzejak

ARI Id

1664660257253_2607654

Access

Not Available Free

Pages

29-39

DOI

10.1007/BFb0053012

Chapter URL

https://rd.springer.com/chapter/10.1007/BFb0053012

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Chapters/Headings	Author(s)	Pages	Info
Front Matter		I-4
Introduction to the theory of complexity and approximation algorithms	Thomas Jansen	5-28
Introduction to randomized algorithms	Artur Andrzejak	29-39
Derandomization	Detlef Sieling	41-61
Proof checking and non-approximability	Stefan Hougardy	63-82
Proving the PCP-Theorem	Volker Heun; Wolfgang Merkle; Ulrich Weigand	83-160
Parallel repetition of MIP(2, 1) systems	Clemens Gröpl; Martin Skutella	161-177
Bounds for approximating MaxLinEq3-2 and MaxEkSat	Sebastian Seibert; Thomas Wilke	179-211
Deriving non-approximability results by reductions	Claus Rick; Hein Röhrig	213-233
Optimal non-approximability of MaxClique	Mastin Mundhenk; Anna Slobodová	235-248
The hardness of approximating set cover	Alexander Wolff	249-262
Semidefinite programming and its applications to approximation algorithms	Thomas Hofmeister; Martin Hühne	263-298
Dense instances of hard optimization problems	Katja Wolf	299-311
Polynomial time approximation schemes for geometric optimization problems in euclidean metric spaces	Richard Mayr; Annette Schelten	313-323
Back Matter		325-334
Chapters/Headings	Author(s)	Pages	Info

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