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Abstract: Bibliography for Lectures 8, 9, and 10 On multicuts, see Handout 6. You can learn more about positive semidefinite matrices from the book by Horn and Johnson [6]. The use of semidefinite programming in combinatorial optimization was pioneered first by Lov'asz [10] (for a special case), and then by Grotschel, Lov'asz, and Schrijver in their monumental work on the ellipsoid algorithm (see [5]). Interior point methods for semidefinite programming were presented by Nesterov and Nemirovskii (see... (Update)
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0.0: Efficient Approximation Algorithms for Some Semidefinite Programs - Lu (1996) (Correct)
0.0: Improved Approximation Algorithms for Maximum Cut and.. - Goemans, Williamson (1995) (Correct)
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BibTeX entry: (Update)
@misc{ rabani-approximation,
author = "Yuval Rabani",
title = "Approximation Algorithms. Bibliography for Lectures 8,9,10",
url = "citeseer.ist.psu.edu/rabani95approximation.html" }
Citations (may not include all citations):230 Interior point methods in semidefinite programming with appl.. - Alizadeh - 1995
115 Approximating the value of two prover proof systems (context) - Feige, Goemans
106 approximation algorithms for MAX CUT and MAX 2SAT (context) - Goemans, Williamson
2 Bin packing can be solved within 1 + ffl in linear time (context) - Vega, Lueker - 1981
Documents on the same site (http://www.cs.technion.ac.il/~rabani/236521.95.wi.html): More
Approximation algorithm - Bibliography for Lecture 5 - Rabani (1995) (Correct)
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