431 search results - page 28 / 87 » Observational Learning with Modular Networks |
PERCOM
2007
ACM
14 years 7 months ago
2007
ACM
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
We present a generalization of the nonnegative matrix factorization (NMF), where a multilayer generative network with nonnegative weights is used to approximate the observed nonne...
CEC
2009
IEEE
14 years 2 months ago
2009
IEEE
Abstract— The bacterial genome is well understood by biologists. Although its efficiency and adaptability should make it a good model for evolutionary algorithms, the bacterial ...
UAI
2003
13 years 9 months ago
2003
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
IJAR
2010
13 years 6 months ago
2010
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...