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PAKDD
2005
ACM
94views Data Mining» more  PAKDD 2005»
16 years 4 days ago
Progressive Sampling for Association Rules Based on Sampling Error Estimation
We explore in this paper a progressive sampling algorithm, called Sampling Error Estimation (SEE), which aims to identify an appropriate sample size for mining association rules. S...
Kun-Ta Chuang, Ming-Syan Chen, Wen-Chieh Yang
ACMMSP
2004
ACM
101views Hardware» more  ACMMSP 2004»
16 years 2 days ago
Metrics and models for reordering transformations
Irregular applications frequently exhibit poor performance on contemporary computer architectures, in large part because of their inefficient use of the memory hierarchy. Runtime ...
Michelle Mills Strout, Paul D. Hovland
ICTAI
2002
IEEE
15 years 11 months ago
Machine Learning for Software Engineering: Case Studies in Software Reuse
There are many machine learning algorithms currently available. In the 21st century, the problem no longer lies in writing the learner, but in choosing which learners to run on a ...
Justin S. Di Stefano, Tim Menzies
APGV
2007
ACM
124views Visualization» more  APGV 2007»
15 years 10 months ago
A perceptive evaluation of volume rendering techniques
The display of space filling data is still a challenge for the community of visualization. Direct Volume Rendering (DVR) is one of the most important techniques developed to achie...
Christian Boucheny, Georges-Pierre Bonneau, Jacque...
AUSDM
2006
Springer
118views Data Mining» more  AUSDM 2006»
15 years 10 months ago
Efficiently Identifying Exploratory Rules' Significance
How to efficiently discard potentially uninteresting rules in exploratory rule discovery is one of the important research foci in data mining. Many researchers have presented algor...
Shiying Huang, Geoffrey I. Webb