8970 search results - page 12 / 1794 » Learning to Learn Causal Models |
ICA
2010
Springer
15 years 23 days ago
2010
Springer
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
ICML
2010
IEEE
15 years 22 days ago
2010
IEEE
The importance of bringing causality into play when designing feature selection methods is more and more acknowledged in the machine learning community. This paper proposes a filt...
ICML
2004
IEEE
16 years 14 days ago
2004
IEEE
We describe a class of causal, discrete latent variable models called Multiple Multiplicative Factor models (MMFs). A data vector is represented in the latent space as a vector of...
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JMLR
2010
14 years 6 months ago
2010
Current methods for causal structure learning tend to be computationally intensive or intractable for large datasets. Some recent approaches have speeded up the process by first m...
HICSS
2003
IEEE
15 years 5 months ago
2003
IEEE
Basically, instrumental conditioning is learning through consequences: Behavior that produces positive results (high “instrumental response”) is reinforced, and that which pro...