57 search results - page 4 / 12 » Active learning in heteroscedastic noise |
74
Voted
MICAI
2004
Springer
15 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...
67
Voted
IJON
2002
14 years 10 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...
80
Voted
ICDM
2005
IEEE
15 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)...
86
Voted
ICML
2004
IEEE
15 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
16 years 4 days 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...