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Könyv Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques Chandra Chekuri

Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques

8th International Workshop on Approximation Algorithms for Compinatorial Optimization Problems, APPROX 2005 and 9th International Workshop on Randomization and Computation, RANDOM 2005, Berkeley, CA,

Szerző: Chandra Chekuri, Klaus Jansen, José D. P. Rolim, Luca Trevisan
Nyelv: Angol
Kötés: Puha kötésű
Kiadó: Springer, Berlin
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
19 325 Ft
This book constitutes the joint refereed proceedings of the 8th International Workshop on Approximat...

Információk a könyvről

Szerző
Chandra Chekuri, Klaus Jansen, José D. P. Rolim, Luca Trevisan
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2005
oldal
495
EAN
9783540282396
ISBN
3540282394
Enbook ID
01560986
Kiadó
Springer, Berlin
Súly
712
Méretek
155 x 235 x 26

Teljes leírás

This book constitutes the joint refereed proceedings of the 8th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2005 and the 9th International Workshop on Randomization and Computation, RANDOM 2005, held in Berkeley, CA, USA in August 2005.§The volume contains 41 carefully reviewed papers, selected by the two program committees from a total of 101 submissions. Among the issues addressed 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 design and routing, packing and covering, scheduling, design and analysis of randomized algorithms, randomized complexity theory, pseudorandomness and derandomization, random combinatorial structures, random walks/Markov chains, expander graphs and randomness extractors, probabilistic proof systems, random projections and embeddings, error-correcting codes, average-case analysis, property testing, computational learning theory, and other applications of approximation and randomness.

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