765 search results - page 1 / 153 » Learning from Multiple Annotators with Gaussian Processes |
ICANN
2011
Springer
12 years 8 months ago
2011
Springer
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
Many real-world classification tasks involve the prediction of multiple, inter-dependent class labels. A prototypical case of this sort deals with prediction of a sequence of labe...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
MLMI
2007
Springer
13 years 11 months ago
2007
Springer
We describe a method for recovering 3D human body pose from silhouettes. Our model is based on learning a latent space using the Gaussian Process Latent Variable Model (GP-LVM) [1]...