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Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques

Posted By: DZ123
Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques

Chandra Chekuri, Klaus Jansen, José D.P. Rolim, "Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques"
English | 2005 | ISBN: 3540282394 | PDF | pages: 505 | 4.9 mb

This volume contains the papers presented at the 8th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2005) and the 9th International Workshop on Randomization and Computation(RANDOM2005),whichtookplaceconcurrentlyattheUniversity of California in Berkeley, on August 22-24, 2005. APPROX focuses on algori- mic and complexity issues surrounding the development of e?cient approximate solutions to computationally hard problems, and APPROX 2005 was the eighth in the series after Aalborg (1998), Berkeley (1999), Saarbru ¨cken (2000), Ber- ley (2001),Rome (2002),Princeton(2003),and Cambridge(2004).RANDOM is concerned with applications of randomness to computational and combinatorial problems, and RANDOM 2005 was the ninth workshop in the series foll- ing Bologna (1997), Barcelona (1998), Berkeley(1999), Geneva (2000), Berkeley (2001), Harvard (2002), Princeton (2003), and Cambridge (2004). Topics of interest for APPROX and RANDOM are: design and analysis of approximation algorithms, hardness of approximation, small space and data streaming algorithms, sub-linear time algorithms, embeddings and metric space methods, mathematical programming methods, coloring and partitioning, cuts and connectivity, geometric problems, game theory and applications, network designandrouting,packingand covering,scheduling,designandanalysisofr- domized algorithms, randomized complexity theory, pseudorandomness and - randomization,random combinatorialstructures, randomwalks/Markovchains, expander graphs and randomness extractors, probabilistic proof systems, r- dom projections and embeddings, error-correcting codes, average-case analysis, property testing, computational learning theory, and other applications of - proximation and randomness. The volume contains 20 contributed papers selected by the APPROX P- gram Committee out of 50 submissions, and 21 contributed papers selected by the RANDOM Program Committee out of 51 submissions.