153 search results - page 15 / 31 » Learning a Continuous Hidden Variable Model for Binary Data |
JMLR
2010
13 years 2 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
SAC
2009
ACM
14 years 2 months ago
2009
ACM
We introduce a new data mining problem: mining truth tables in binary datasets. Given a matrix of objects and the properties they satisfy, a truth table identifies a subset of pr...
GECCO
2007
Springer
14 years 1 months ago
2007
Springer
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
CIDU
2010
13 years 5 months ago
2010
Abstract. Climate models are complex mathematical models designed by meteorologists, geophysicists, and climate scientists to simulate and predict climate. Given temperature predic...
CVPR
1999
IEEE
14 years 9 months ago
1999
IEEE
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...