288 search results - page 10 / 58 » Robust Regression and Lasso |
CORR
2011
Springer
12 years 11 months ago
2011
Springer
We propose Shotgun, a parallel coordinate descent algorithm for minimizing L1regularized losses. Though coordinate descent seems inherently sequential, we prove convergence bounds...
ICASSP
2010
IEEE
13 years 8 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...
NECO
2002
13 years 7 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...
CSDA
2006
13 years 8 months ago
2006
The least squares linear regression estimator is well-known to be highly sensitive to unusual observations in the data, and as a result many more robust estimators have been propo...
ICASSP
2010
IEEE
13 years 8 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 ...