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ICANN
2010
Springer
15 years 4 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...
118
Voted
ICANN
2010
Springer
15 years 4 months ago
Assessing Statistical Reliability of LiNGAM via Multiscale Bootstrap
Structural equation models have been widely used to study causal relationships between continuous variables. Recently, a non-Gaussian method called LiNGAM was proposed to discover ...
Yusuke Komatsu, Shohei Shimizu, Hidetoshi Shimodai...
160
Voted
CVPR
2010
IEEE
15 years 3 months ago
Robust RVM regression using sparse outlier model
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
CVPR
2010
IEEE
15 years 3 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
138
Voted
ICASSP
2010
IEEE
15 years 3 months ago
Image-quality prediction of synthetic aperture sonar imagery
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
David P. Williams