125 search results - page 2 / 25 » Adaptive methods for sequential importance sampling with app... |
ICIP
2009
IEEE
14 years 6 months ago
2009
IEEE
We present a multi modal sequential importance resampling particle filter algorithm for object tracking. We consider a hidden state sequence linked to several observation sequence...
NIPS
2007
13 years 6 months ago
2007
Learning in real-world domains often requires to deal with continuous state and action spaces. Although many solutions have been proposed to apply Reinforcement Learning algorithm...
NIPS
2007
13 years 6 months ago
2007
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
BIBM
2007
IEEE
13 years 11 months ago
2007
IEEE
With the wide application of green fluorescent protein (GFP) in the study of live cells, there is a surging need for the computer-aided analysis on the huge amount of image seque...
ECML
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....