34 search results - page 3 / 7 » Robust RVM regression using sparse outlier model |
NECO
2002
13 years 5 months ago
2002
In the presence of a heavy-tail noise distribution, regression becomes much more di cult. Traditional robust regression methods assume that the noise distribution is symmetric and...
CORR
2010
Springer
13 years 2 months ago
2010
Springer
In the recent work of Candes et al, the problem of recovering low rank matrix corrupted by i.i.d. sparse outliers is studied and a very elegant solution, principal component pursui...
JMLR
2002
13 years 5 months ago
2002
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
ICIP
2006
IEEE
14 years 7 months ago
2006
IEEE
In this paper we propose a set of algorithms that combine the anisotropic smoothing using the heat kernel with the outlier rejection capability of robust statistics. The proposed ...
NIPS
2007
13 years 7 months ago
2007
We propose a Gaussian process (GP) framework for robust inference in which a GP prior on the mixing weights of a two-component noise model augments the standard process over laten...