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» Using Data Mining to Estimate Missing Sensor Data
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KDD
2004
ACM
139views Data Mining» more  KDD 2004»
16 years 6 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
ICASSP
2009
IEEE
16 years 22 days ago
Sparse imputation for noise robust speech recognition using soft masks
In previous work we introduced a new missing data imputation method for ASR, dubbed sparse imputation. We showed that the method is capable of maintaining good recognition accurac...
Jort F. Gemmeke, Bert Cranen
INFFUS
2011
82views more  INFFUS 2011»
14 years 9 months ago
Joint ego-motion and road geometry estimation
We provide a sensor fusion framework for solving the problem of joint ego-motion and road geometry estimation. More specifically we employ a sensor fusion framework to make syste...
Christian Lundquist, Thomas B. Schön
AAAI
2007
15 years 8 months ago
Learning Large Scale Common Sense Models of Everyday Life
Recent work has shown promise in using large, publicly available, hand-contributed commonsense databases as joint models that can be used to infer human state from day-to-day sens...
William Pentney, Matthai Philipose, Jeff A. Bilmes...
SIGMOD
2005
ACM
150views Database» more  SIGMOD 2005»
16 years 6 months ago
BRAID: Stream Mining through Group Lag Correlations
The goal is to monitor multiple numerical streams, and determine which pairs are correlated with lags, as well as the value of each such lag. Lag correlations (and anticorrelation...
Yasushi Sakurai, Spiros Papadimitriou, Christos Fa...