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ICASSP
2011
IEEE
12 years 8 months ago
How efficient is estimation with missing data?
In this paper, we present a new evaluation approach for missing data techniques (MDTs) where the efficiency of those are investigated using listwise deletion method as reference....
Seliz G. Karadogan, Letizia Marchegiani, Lars Kai ...
DASFAA
2007
IEEE
234views Database» more  DASFAA 2007»
13 years 11 months ago
Estimating Missing Data in Data Streams
Networks of thousands of sensors present a feasible and economic solution to some of our most challenging problems, such as real-time traffic modeling, military sensing and trackin...
Nan Jiang, Le Gruenwald
NIPS
1994
13 years 5 months ago
Efficient Methods for Dealing with Missing Data in Supervised Learning
We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation ...
Volker Tresp, Ralph Neuneier, Subutai Ahmad
AMC
2006
173views more  AMC 2006»
13 years 4 months ago
Data envelopment analysis with missing values: An interval DEA approach
Missing values in inputs, outputs cannot be handled by the original data envelopment analysis (DEA) models. In this paper we introduce an approach based on interval DEA that allow...
Yannis G. Smirlis, Elias K. Maragos, Dimitris K. D...
DMSN
2010
ACM
13 years 5 months ago
DEMS: a data mining based technique to handle missing data in mobile sensor network applications
In Mobile Sensor Network (MSN) applications, sensors move to increase the area of coverage and/or to compensate for the failure of other sensors. In such applications, loss or cor...
Le Gruenwald, Md. Shiblee Sadik, Rahul Shukla, Han...