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BMCBI
2007
138views more  BMCBI 2007»
13 years 7 months ago
A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic
Background: A key challenge in metabonomics is to uncover quantitative associations between multidimensional spectroscopic data and biochemical measures used for disease risk asse...
Aki Vehtari, Ville-Petteri Mäkinen, Pasi Soin...
BMCBI
2010
154views more  BMCBI 2010»
13 years 7 months ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...
ICPR
2006
IEEE
14 years 8 months ago
Shape Alignment by Learning a Landmark-PDM Coupled Model
This paper revisits the model-based approaches for groupwise shape alignment. The key contribution is modeling the landmarks instead of considering them as nodes sliding along the...
Yifeng Jiang, Jun Xie, Hung-Tat Tsui
ICML
2009
IEEE
14 years 8 months ago
Identifying suspicious URLs: an application of large-scale online learning
This paper explores online learning approaches for detecting malicious Web sites (those involved in criminal scams) using lexical and host-based features of the associated URLs. W...
Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffr...
CVPR
2012
IEEE
11 years 10 months ago
Unsupervised learning of translation invariant occlusive components
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
Zhenwen Dai, Jörg Lücke