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» Robust estimation for sparse data
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ICCV
2003
IEEE
15 years 11 months ago
Robust Regression with Projection Based M-estimators
The robust regression techniques in the RANSAC family are popular today in computer vision, but their performance depends on a user supplied threshold. We eliminate this drawback ...
Haifeng Chen, Peter Meer
ICASSP
2008
IEEE
15 years 4 months ago
Robust correlation analysis with an application to functional MRI
Correlation is often used to measure the similarity between signals and is an important tool in signal and image processing. In some applications it is common that signals are cor...
Joakim Rydell, Magnus Borga, Hans Knutsson
KDD
2007
ACM
156views Data Mining» more  KDD 2007»
15 years 10 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...
BMCBI
2005
127views more  BMCBI 2005»
14 years 9 months ago
Are scale-free networks robust to measurement errors?
Background: Many complex random networks have been found to be scale-free. Existing literature on scale-free networks has rarely considered potential false positive and false nega...
Nan Lin, Hongyu Zhao
ICASSP
2009
IEEE
15 years 4 months ago
A criterion for the enhancement of time-frequency masks in missing data recognition
Despite their effectiveness for robust speech processing, missing data techniques are vulnerable to errors in the classification of the input speech signal’s time-frequency poi...
Daniel Pullella, Roberto Togneri