32 search results - page 6 / 7 » Multi-Task Learning of Gaussian Graphical Models |
SDM
2009
SIAM
14 years 4 months ago
2009
SIAM
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
COLT
2010
Springer
13 years 5 months ago
2010
Springer
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
UAI
2008
13 years 8 months ago
2008
An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used ...
NIPS
2008
13 years 8 months ago
2008
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...