343 search results - page 35 / 69 » Imitation Learning Using Graphical Models |
ECCV
2010
Springer
13 years 6 months ago
2010
Springer
Abstract. This work focuses on characterizing scenery images. We semantically divide the objects in natural landscape scenes into background and foreground and show that the shapes...
ICML
2008
IEEE
14 years 9 months ago
2008
IEEE
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and pra...
ICIG
2009
IEEE
13 years 6 months ago
2009
IEEE
Optical flow estimation is one of the main subjects in computer vision. Many methods developed to compute the motion fields are built using standard heuristic formulation. In this...
UAI
2008
13 years 10 months ago
2008
We introduce a new type of graphical model called a `cumulative distribution network' (CDN), which expresses a joint cumulative distribution as a product of local functions. ...
SODA
2001
ACM
13 years 10 months ago
2001
ACM
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...