288 search results - page 1 / 58 » Robust Regression and Lasso |
NIPS
2008
13 years 6 months ago
2008
We consider robust least-squares regression with feature-wise disturbance. We show that this formulation leads to tractable convex optimization problems, and we exhibit a particul...
NN
2010
Springer
12 years 11 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...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
CSDA
2007
13 years 4 months ago
2007
The Lasso is an attractive regularisation method for high dimensional regression. It combines variable selection with an efficient computational procedure. However, the rate of co...
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
We present a new algorithm for minimizing a convex loss-function subject to regularization. Our framework applies to numerous problems in machine learning and statistics; notably,...