216 search results - page 28 / 44 » Learning in Gaussian Markov random fields |
137
Voted
ICML
2010
IEEE
15 years 4 months ago
2010
IEEE
Learning temporal causal graph structures from multivariate time-series data reveals important dependency relationships between current observations and histories, and provides a ...
152
click to vote
ICML
2010
IEEE
15 years 4 months ago
2010
IEEE
Learning undirected graphical models such as Markov random fields is an important machine learning task with applications in many domains. Since it is usually intractable to learn...
143
Voted
UAI
2004
15 years 4 months ago
2004
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
189
Voted
CIVR
2008
Springer
15 years 5 months ago
2008
Springer
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
130
Voted
TMI
2008
15 years 3 months ago
2008
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...