34 search results - page 1 / 7 » Robust RVM regression using sparse outlier model |
CVPR
2010
IEEE
13 years 9 months ago
2010
IEEE
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
CORR
2010
Springer
13 years 9 months ago
2010
Springer
This paper studies the outlier detection problem from the point of view of penalized regressions. Our regression model adds one mean shift parameter for each of the n data points....
ICASSP
2010
IEEE
13 years 9 months ago
2010
IEEE
In this paper, we develop algorithms for robust linear regression by leveraging the connection between the problems of robust regression and sparse signal recovery. We explicitly ...
ICASSP
2010
IEEE
13 years 9 months ago
2010
IEEE
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
NN
2010
Springer
13 years 4 months ago
2010
Springer
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...