339 search results - page 21 / 68 » Approximate Inference in Probabilistic Graphical Models with... |
74
Voted
IJCAI
2003
14 years 11 months ago
2003
We present a new general framework for online istic plan recognition called the Abstract Hidden Markov Memory Model (AHMEM). The l is an extension of the existing Abstract Hidden ...
IJON
2010
14 years 4 months ago
2010
This paper presents a novel methodology to infer parameters of probabilistic models whose output noise is a Student-t distribution. The method is an extension of earlier work for ...
JMLR
2010
14 years 4 months ago
2010
It is probably fair to say that exact inference in graphical models is considered a solved problem, at least regarding its computational complexity: it is exponential in the treew...
86
Voted
CVPR
2005
IEEE
15 years 11 months ago
2005
IEEE
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
JMLR
2006
14 years 9 months ago
2006
We present a new framework based on walks in a graph for analysis and inference in Gaussian graphical models. The key idea is to decompose the correlation between each pair of var...