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» An extension of the ICA model using latent variables
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NIPS
2008
13 years 11 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
SADM
2010
141views more  SADM 2010»
13 years 4 months ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman
SIGECOM
2009
ACM
118views ECommerce» more  SIGECOM 2009»
14 years 4 months ago
Modeling volatility in prediction markets
There is significant experimental evidence that prediction markets are efficient mechanisms for aggregating information and are more accurate in forecasting events than tradition...
Nikolay Archak, Panagiotis G. Ipeirotis
ICSR
2004
Springer
14 years 3 months ago
Feature Dependency Analysis for Product Line Component Design
Analyzing commonalities and variabilities among products of a product line is an essential activity for product line asset development. A feature-oriented approach to commonality a...
Kwanwoo Lee, Kyo Chul Kang
ICPR
2004
IEEE
14 years 11 months ago
Joint Spatial and Temporal Structure Learning for Task based Control
We present an example of a joint spatial and temporal task learning algorithm that results in a generative model that has applications for on-line visual control. We review work o...
Hilary Buxton, Kingsley Sage