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» Streaming Algorithms Measured in Terms of the Computed Quant...
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STOC
2003
ACM
141views Algorithms» more  STOC 2003»
14 years 9 months ago
Better streaming algorithms for clustering problems
We study clustering problems in the streaming model, where the goal is to cluster a set of points by making one pass (or a few passes) over the data using a small amount of storag...
Moses Charikar, Liadan O'Callaghan, Rina Panigrahy
IPPS
2005
IEEE
14 years 2 months ago
Stream PRAM
Parallel random access memory, or PRAM, is a now venerable model of parallel computation that that still retains its usefulness for the design and analysis of parallel algorithms....
Darrell R. Ulm, Michael Scherger
GECCO
2007
Springer
124views Optimization» more  GECCO 2007»
14 years 14 days ago
Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms
The Negative Slope Coefficient (nsc) is an empirical measure of problem hardness based on the analysis of offspring-fitness vs. parent-fitness scatterplots. The nsc has been teste...
Riccardo Poli, Leonardo Vanneschi
ISCC
1999
IEEE
14 years 26 days ago
On Network Survivability Algorithms Based on Trellis Graph Transformations
Due to the wide range of services being supported, telecommunications networks are loaded with massive quantities of information. This stimulates extra concern for network surviva...
Soulla Louca, Andreas Pitsillides, George Samaras
ASC
2008
13 years 8 months ago
Info-fuzzy algorithms for mining dynamic data streams
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...