1760 search results - page 24 / 352 » Learning from Partial Observations |
CORR
2010
Springer
13 years 7 months ago
2010
Springer
We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...
ECML
2005
Springer
14 years 1 months ago
2005
Springer
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
ICML
1999
IEEE
13 years 12 months ago
1999
IEEE
Developing automated agents that intelligently perform complex real world tasks is time consuming and expensive. The most expensive part of developing these intelligent task perfo...
CVPR
2009
IEEE
15 years 2 months ago
2009
IEEE
We propose a novel approach to designing algorithms for
object tracking based on fusing multiple observation models.
As the space of possible observation models is too large
for...
IDEAL
2000
Springer
13 years 11 months ago
2000
Springer
Observational learning algorithm is an ensemble algorithm where each network is initially trained with a bootstrapped data set and virtual data are generated from the ensemble for ...