106 search results - page 19 / 22 » The max-min hill-climbing Bayesian network structure learnin... |
98
Voted
ICASSP
2008
IEEE
15 years 4 months ago
2008
IEEE
This paper presents a new framework for accumulating beliefs in spoken dialogue systems. The technique is based on updating a Bayesian Network that represents the underlying state...
NIPS
2008
14 years 11 months ago
2008
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
UAI
2001
14 years 11 months ago
2001
In this paper we present a method of computing the posterior probability of conditional independence of two or more continuous variables from data, examined at several resolutions...
KDD
2010
ACM
15 years 1 months ago
2010
ACM
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
CVPR
2000
IEEE
15 years 11 months ago
2000
IEEE
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and analysis of figure motion has employed eith...