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» Measuring independence of datasets
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UAI
2003
15 years 8 months ago
Large-Sample Learning of Bayesian Networks is NP-Hard
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
ICANN
2010
Springer
15 years 7 months ago
Discovery of Exogenous Variables in Data with More Variables Than Observations
Many statistical methods have been proposed to estimate causal models in classical situations with fewer variables than observations. However, modern datasets including gene expres...
Yasuhiro Sogawa, Shohei Shimizu, Aapo Hyvärin...
CVPR
2010
IEEE
15 years 6 months ago
Modeling pixel means and covariances using factorized third-order boltzmann machines
Learning a generative model of natural images is a useful way of extracting features that capture interesting regularities. Previous work on learning such models has focused on me...
Marc Aurelio Ranzato, Geoffrey E. Hinton
BMCBI
2008
154views more  BMCBI 2008»
15 years 6 months ago
Sequence based residue depth prediction using evolutionary information and predicted secondary structure
Background: Residue depth allows determining how deeply a given residue is buried, in contrast to the solvent accessibility that differentiates between buried and solvent-exposed ...
Hua Zhang, Tuo Zhang, Ke Chen 0003, Shiyi Shen, Ji...
CGF
2010
148views more  CGF 2010»
15 years 6 months ago
Hardware-Assisted Projected Tetrahedra
We present a flexible and highly efficient hardware-assisted volume renderer grounded on the original Projected Tetrahedra (PT) algorithm. Unlike recent similar approaches, our me...
André Maximo, Ricardo Marroquim, Ricardo C....