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KDD
2006
ACM
150views Data Mining» more  KDD 2006»
14 years 8 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 7 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
14 years 1 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 12 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 8 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...