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KDD
2006
ACM
150views Data Mining» more  KDD 2006»
14 years 6 months ago
Maximally informative k-itemsets and their efficient discovery
In this paper we present a new approach to mining binary data. We treat each binary feature (item) as a means of distinguishing two sets of examples. Our interest is in selecting ...
Arno J. Knobbe, Eric K. Y. Ho
FGCS
2007
86views more  FGCS 2007»
13 years 6 months ago
A grid-based approach for enterprise-scale data mining
Abstract— We describe a grid-based approach for enterprisescale data mining that leverages database technology for I/O parallelism, and on-demand compute servers for compute para...
Ramesh Natarajan, Radu Sion, Thomas Phan
NETGAMES
2005
ACM
13 years 11 months ago
Game server selection for multiple players
The increase in power and connectivity of computers has enabled a growth in network games, with many games having numerous servers to which a player can connect. The game server s...
Steven Gargolinski, Christopher St. Pierre, Mark C...
GI
1998
Springer
13 years 10 months ago
Self-Organizing Data Mining
"KnowledgeMiner" was designed to support the knowledge extraction process on a highly automated level. Implemented are 3 different GMDH-type self-organizing modeling algo...
Frank Lemke, Johann-Adolf Müller
HPCA
2004
IEEE
14 years 6 months ago
Reducing Branch Misprediction Penalty via Selective Branch Recovery
Branch misprediction penalty consists of two components: the time wasted on mis-speculative execution until the mispredicted branch is resolved and the time to restart the pipelin...
Amit Gandhi, Haitham Akkary, Srikanth T. Srinivasa...