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JMLR
2010
134views more  JMLR 2010»
13 years 2 months ago
Bayesian Algorithms for Causal Data Mining
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...
TMI
2008
92views more  TMI 2008»
13 years 8 months ago
Using Perturbation Theory to Compute the Morphological Similarity of Diffusion Tensors
Computing the morphological similarity of diffusion tensors (DTs) at neighboring voxels within a DT image, or at corresponding locations across different DT images, is a fundamenta...
Ravi Bansal, Lawrence H. Staib, Dongrong Xu, Andre...
BMCBI
2007
128views more  BMCBI 2007»
13 years 8 months ago
Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assess
Background: Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. Howeve...
Paolo Ferragina, Raffaele Giancarlo, Valentina Gre...
AAAI
1996
13 years 9 months ago
Building Classifiers Using Bayesian Networks
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
Nir Friedman, Moisés Goldszmidt
ICASSP
2011
IEEE
12 years 11 months ago
Joint Bayesian removal of impulse and background noise
We present a method for the removal of noise including nonGaussian impulses from a signal. Impulse noise is removed jointly a homogenous Gaussian noise floor using a Gabor regres...
James Murphy, Simon J. Godsill