34 search results - page 2 / 7 » Robust RVM regression using sparse outlier model |
CSDA
2007
13 years 5 months ago
2007
In this paper we address the problem of selecting variables or features in a regression model in the presence of both additive (vertical) and leverage outliers. Since variable sel...
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
The recent upsurge of research toward compressive sampling and parsimonious signal representations hinges on signals being sparse, either naturally, or, after projecting them on a...
CORR
2012
Springer
12 years 27 days ago
2012
Springer
This paper develops theoretical results regarding noisy 1-bit compressed sensing and sparse binomial regression. We demonstrate that a single convex program gives an accurate estim...
INFORMATICALT
2011
13 years 5 days ago
2011
It is well known that in situations involving the study of large datasets where influential observations or outliers maybe present, regression models based on the Maximum Likeliho...
ICML
2004
IEEE
14 years 6 months ago
2004
IEEE
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...