57 search results - page 4 / 12 » Active learning in heteroscedastic noise |
MICAI
2004
Springer
14 years 3 months ago
2004
Springer
We present an optimization algorithm that combines active learning and locally-weighted regression to find extreme points of noisy and complex functions. We apply our algorithm to...
IJON
2002
13 years 9 months ago
2002
The `Bussgang' algorithm is one among the most known blind deconvolution techniques in the adaptive signal processing literature. It relies on a Bayesian estimator of the sou...
ICDM
2005
IEEE
14 years 3 months ago
2005
IEEE
Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert)...
ICML
2004
IEEE
14 years 3 months ago
2004
IEEE
The paper is concerned with two-class active learning. While the common approach for collecting data in active learning is to select samples close to the classification boundary,...
ECCV
2008
Springer
14 years 11 months ago
2008
Springer
As computer vision research considers more object categories and greater variation within object categories, it is clear that larger and more exhaustive datasets are necessary. How...