111 search results - page 4 / 23 » Causal Graphical Models with Latent Variables: Learning and ... |
102
Voted
GRC
2010
IEEE
15 years 22 days ago
2010
IEEE
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
NIPS
2000
15 years 29 days ago
2000
We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
NIPS
1997
15 years 29 days ago
1997
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
75
Voted
ICTAI
2009
IEEE
15 years 6 months ago
2009
IEEE
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...
99
Voted
SPEECH
1998
14 years 11 months ago
1998
We consider the problem of obtaining a reduced dimension representation of electropalatographic (EPG) data. An unsupervised learning approach based on latent variable modelling is...