224 search results - page 3 / 45 » Gaussian processes and limiting linear models |
ICONIP
2007
13 years 7 months ago
2007
Abstract. An effective way to examine causality is to conduct an experiment with random assignment. However, in many cases it is impossible or too expensive to perform controlled ...
ICA
2010
Springer
13 years 6 months 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...
ICARCV
2008
IEEE
14 years 7 days ago
2008
IEEE
— We consider a discrete-time dynamical system with Boolean and continuous states, with the continuous state propagating linearly in the continuous and Boolean state variables, a...
NIPS
2000
13 years 7 months ago
2000
We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets. The method is based on a...
NIPS
2003
13 years 7 months ago
2003
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...