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JMLR
2010
202views more  JMLR 2010»
13 years 2 months ago
Learning the Structure of Deep Sparse Graphical Models
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...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
ICNC
2009
Springer
14 years 8 days ago
Knowledge Acquisition Approach Based on Rough Set and Artificial Neural Network in Product Design Process
In this paper, product structure is taken as knowledge acquisition point, and the effective knowledge acquisition path is discussed by establishing the associated relationship bet...
Changfeng Yuan, Wanlei Wang, Yan Chen
NIPS
2000
13 years 9 months ago
Structure Learning in Human Causal Induction
We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
Joshua B. Tenenbaum, Thomas L. Griffiths
CMSB
2011
Springer
12 years 7 months ago
The singular power of the environment on stochastic nonlinear threshold Boolean automata networks
Abstract. This paper tackles theoretically the question of the structural stability of biological regulation networks subjected to the influence of their environment. The model of...
Jacques Demongeot, Sylvain Sené
HICSS
2006
IEEE
62views Biometrics» more  HICSS 2006»
14 years 1 months ago
Structuration, Emancipation and Democracy
The study investigates the role of ICT in facilitating democracy. The role of ICT in maintaining status quo, or structure of the society can be explained using structuration theor...
Ook Lee