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TSP
2010
13 years 2 months ago
Distributed sampling of signals linked by sparse filtering: theory and applications
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetter...
ER
2006
Springer
135views Database» more  ER 2006»
13 years 11 months ago
Towards Automatic Evaluation of Learning Object Metadata Quality
Thanks to recent developments on automatic generation of metadata and interoperability between repositories, the production, management and consumption of learning object metadata ...
Xavier Ochoa, Erik Duval
ISVLSI
2008
IEEE
143views VLSI» more  ISVLSI 2008»
14 years 2 months ago
BTB Access Filtering: A Low Energy and High Performance Design
Powerful branch predictors along with a large branch target buffer (BTB) are employed in superscalar processors for instruction-level parallelism exploitation. However, the large ...
Shuai Wang, Jie Hu, Sotirios G. Ziavras
KDD
2009
ACM
227views Data Mining» more  KDD 2009»
14 years 8 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
PROMISE
2010
13 years 2 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies