26 search results - page 1 / 6 » Bayesian regression with input noise for high dimensional da... |
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
CVPR
2008
IEEE
15 years 11 months ago
2008
IEEE
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...
IJCAI
1997
14 years 11 months ago
1997
Many of the challenges faced by the £eld of Computational Intelligence in building intelligent agents, involve determining mappings between numerous and varied sensor inputs and ...
NIPS
2001
14 years 11 months ago
2001
Estimating insurance premia from data is a difficult regression problem for several reasons: the large number of variables, many of which are discrete, and the very peculiar shape...
ICML
2004
IEEE
15 years 10 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...