922 search results - page 27 / 185 » Learning Gaussian Process Models from Uncertain Data |
NIPS
1998
13 years 8 months ago
1998
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
ICIAR
2010
Springer
13 years 4 months ago
2010
Springer
Image segmentation is a critical low-level visual routine for robot perception. However, most image segmentation approaches are still too slow to allow real-time robot operation. I...
ICONIP
2007
13 years 8 months ago
2007
Abstract. An effective way to examine causality is to conduct an experiment with random assignment. However, in many cases it is impossible or too expensive to perform controlled ...
APIN
2004
13 years 7 months ago
2004
This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...
NIPS
2008
13 years 8 months ago
2008
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...