153 search results - page 6 / 31 » Learning a Continuous Hidden Variable Model for Binary Data |
ICML
1996
IEEE
14 years 8 months ago
1996
IEEE
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
NIPS
1997
13 years 8 months 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...
SDM
2004
SIAM
13 years 9 months ago
2004
SIAM
We present a novel probabilistic multiple cause model for binary observations. In contrast to other approaches, the model is linear and it infers reasons behind both observed and ...
ARCS
2004
Springer
14 years 28 days ago
2004
Springer
In a pervasive computing environment, one is facing the problem of handling heterogeneous data from different sources, transmitted over heterogeneous channels and presented on het...
ICML
1999
IEEE
14 years 8 months ago
1999
IEEE
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...