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JAIR
1998
198views more  JAIR 1998»
13 years 9 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
MICCAI
2010
Springer
13 years 8 months ago
Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction
Abstract. We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accura...
Li Shen, Yuan Qi, Sungeun Kim, Kwangsik Nho, Jing ...
ICRA
2009
IEEE
122views Robotics» more  ICRA 2009»
13 years 7 months ago
Utilizing reflection properties of surfaces to improve mobile robot localization
Abstract-- A main difficulty that arises in the context of probabilistic localization is the design of an appropriate observation model, i.e., determining the likelihood of a senso...
Maren Bennewitz, Cyrill Stachniss, Sven Behnke, Wo...
ARTMED
2004
118views more  ARTMED 2004»
13 years 9 months ago
Bayesian fluorescence in situ hybridisation signal classification
Previous research has indicated the significance of accurate classification of fluorescence in situ hybridisation (FISH) signals for the detection of genetic abnormalities. Based ...
Boaz Lerner
ICA
2010
Springer
13 years 11 months ago
Binary Sparse Coding
We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
Marc Henniges, Gervasio Puertas, Jörg Bornsch...