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» Introduction to Randomized Algorithms
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VALUETOOLS
2006
ACM
176views Hardware» more  VALUETOOLS 2006»
15 years 11 months ago
How to solve large scale deterministic games with mean payoff by policy iteration
Min-max functions are dynamic programming operators of zero-sum deterministic games with finite state and action spaces. The problem of computing the linear growth rate of the or...
Vishesh Dhingra, Stephane Gaubert
GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
15 years 10 months ago
Diversity as a selection pressure in dynamic environments
Evolutionary algorithms (EAs) are widely used to deal with optimization problems in dynamic environments (DE) [3]. When using EAs to solve DE problems, we are usually interested i...
Lam Thu Bui, Jürgen Branke, Hussein A. Abbass
NOSSDAV
2004
Springer
15 years 10 months ago
Distributed server replication in large scale networks
Quality of service for high-bandwidth or delay-sensitive applications in the Internet, such as streaming media and online games, can be significantly improved by replicating serv...
Bong-Jun Ko, Dan Rubenstein
INFOVIS
2003
IEEE
15 years 10 months ago
Improving Hybrid MDS with Pivot-Based Searching
An algorithm is presented for the visualisation of multidimensional abstract data, building on a hybrid model introduced at InfoVis 2002. The most computationally complex stage of...
Alistair Morrison, Matthew Chalmers
WEA
2010
Springer
316views Algorithms» more  WEA 2010»
15 years 10 months ago
Modularity-Driven Clustering of Dynamic Graphs
Maximizing the quality index modularity has become one of the primary methods for identifying the clustering structure within a graph. As contemporary networks are not static but e...
Robert Görke, Pascal Maillard, Christian Stau...