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» Using Data Mining to Estimate Missing Sensor Data
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KDD
2007
ACM
156views Data Mining» more  KDD 2007»
16 years 6 months ago
Estimating rates of rare events at multiple resolutions
We consider the problem of estimating occurrence rates of rare events for extremely sparse data, using pre-existing hierarchies to perform inference at multiple resolutions. In pa...
Deepak Agarwal, Andrei Z. Broder, Deepayan Chakrab...
JMLR
2010
88views more  JMLR 2010»
15 years 1 months ago
Inference and Learning in Networks of Queues
Probabilistic models of the performance of computer systems are useful both for predicting system performance in new conditions, and for diagnosing past performance problems. The ...
Charles A. Sutton, Michael I. Jordan
CSE
2009
IEEE
15 years 9 months ago
Completely Distributed Low Duty Cycle Communication for Long-Living Sensor Networks
A lifetime of several years for wireless sensor nodes can be achieved if their activity period is minimized. This can be done by using low duty cycle protocols. One of the challeng...
Marcin Brzozowski, Hendrik Salomon, Peter Langendo...
MACOM
2010
15 years 1 months ago
On the Performance of Single LDGM Codes for Iterative Data Fusion over the Multiple Access Channel
One of the applications of wireless sensor networks currently undergoing active research focuses on the scenario where the information generated by a data source S is simultaneousl...
Javier Del Ser, Javier Garcia-Frias, Pedro M. Cres...
KDD
1998
ACM
120views Data Mining» more  KDD 1998»
15 years 10 months ago
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
Tim Oates, David Jensen