613 search results - page 24 / 123 » Learning the Structure of Linear Latent Variable Models |
KDD
2009
ACM
14 years 8 months ago
2009
ACM
Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn ...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
We describe a class of causal, discrete latent variable models called Multiple Multiplicative Factor models (MMFs). A data vector is represented in the latent space as a vector of...
ESANN
2006
13 years 9 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
JMLR
2012
11 years 10 months ago
2012
Many real-world problems are inherently hierarchically structured. The use of this structure in an agent’s policy may well be the key to improved scalability and higher performa...
MLG
2007
Springer
14 years 1 months ago
2007
Springer
: Network topology not only tells about tightly-connected “communities,” but also gives cues on more subtle properties of the vertices. We introduce a simple probabilistic late...