26 search results - page 1 / 6 » Bayesian regression with input noise for high dimensional da... |
ICML
2006
IEEE
14 years 5 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
14 years 6 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
13 years 6 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
13 years 6 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
14 years 5 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...