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» Imputation of missing values for compositional data using cl...
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CSL
2007
Springer
13 years 7 months ago
On noise masking for automatic missing data speech recognition: A survey and discussion
Automatic speech recognition (ASR) has reached very high levels of performance in controlled situations. However, the performance degrades significantly when environmental noise ...
Christophe Cerisara, Sébastien Demange, Jea...
ICAI
2009
13 years 5 months ago
Data Mining in Incomplete Numerical and Categorical Data Sets: A Neuro Fuzzy Approach
- There are many applications dealing with incomplete data sets that take different approaches to making imputations for missing values. Most tackle the problem for numerical input...
Pilar Rey del Castillo, Jesus Cardenosa
IRI
2008
IEEE
14 years 1 months ago
Robust integration of multiple information sources by view completion
There are many applications where multiple data sources, each with its own features, are integrated in order to perform an inference task in an optimal way. Researchers have shown...
Shankara B. Subramanya, Baoxin Li, Huan Liu
CVPR
2010
IEEE
13 years 5 months ago
Efficient computation of robust low-rank matrix approximations in the presence of missing data using the L1 norm
The calculation of a low-rank approximation of a matrix is a fundamental operation in many computer vision applications. The workhorse of this class of problems has long been the ...
Anders Eriksson, Anton van den Hengel
ECML
2007
Springer
14 years 1 months ago
Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
Tapani Raiko, Alexander Ilin, Juha Karhunen