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» Improving Branch Predictors by Correlating on Data Values
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ICVS
2009
Springer
13 years 5 months ago
Boosting with a Joint Feature Pool from Different Sensors
This paper introduces a new way to apply boosting to a joint feature pool from different sensors, namely 3D range data and color vision. The combination of sensors strengthens the ...
Dominik Alexander Klein, Dirk Schulz, Simone Frint...
ICDM
2005
IEEE
137views Data Mining» more  ICDM 2005»
14 years 1 months ago
Leveraging Relational Autocorrelation with Latent Group Models
The presence of autocorrelation provides a strong motivation for using relational learning and inference techniques. Autocorrelation is a statistical dependence between the values...
Jennifer Neville, David Jensen
PKDD
2010
Springer
155views Data Mining» more  PKDD 2010»
13 years 6 months ago
Latent Structure Pattern Mining
Pattern mining methods for graph data have largely been restricted to ground features, such as frequent or correlated subgraphs. Kazius et al. have demonstrated the use of elaborat...
Andreas Maunz, Christoph Helma, Tobias Cramer, Ste...
VLDB
2007
ACM
131views Database» more  VLDB 2007»
14 years 7 months ago
Dissemination of compressed historical information in sensor networks
Sensor nodes are small devices that "measure" their environment and communicate feeds of low-level data values to a base station for further processing and archiving. Dis...
Antonios Deligiannakis, Yannis Kotidis, Nick Rouss...
ICDE
2006
IEEE
142views Database» more  ICDE 2006»
14 years 9 months ago
End-biased Samples for Join Cardinality Estimation
We present a new technique for using samples to estimate join cardinalities. This technique, which we term "end-biased samples," is inspired by recent work in network tr...
Cristian Estan, Jeffrey F. Naughton