142 search results - page 7 / 29 » Learning Graphical Model Structure Using L1-Regularization P... |
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Learning the structure of graphical models is an important task, but one of considerable difficulty when latent variables are involved. Because conditional independences using hid...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...
AAAI
2008
13 years 9 months ago
2008
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
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...
ICRA
2010
IEEE
13 years 5 months ago
2010
IEEE
— We consider the problem of finding sufficiently simple models of high-dimensional physical systems that are consistent with observed trajectories, and using these models to s...