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» An LFT approach to parameter estimation
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BMCBI
2007
138views more  BMCBI 2007»
15 years 6 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...
IPMI
2009
Springer
16 years 7 months ago
A Unified Framework for MR Based Disease Classification
In this paper, we employ an anatomical parameterization of spatial warps to reveal structural differences between medical images of healthy control subjects and disease patients. T...
Kilian M. Pohl, Mert R. Sabuncu
RECOMB
2011
Springer
14 years 9 months ago
Rich Parameterization Improves RNA Structure Prediction
Motivation. Current approaches to RNA structure prediction range from physics-based methods, which rely on thousands of experimentally-measured thermodynamic parameters, to machin...
Shay Zakov, Yoav Goldberg, Michael Elhadad, Michal...
CSDA
2006
98views more  CSDA 2006»
15 years 6 months ago
GS-distributions: A new family of distributions for continuous unimodal variables
The choice of the best-suited statistical distribution for modeling data is not a trivial issue. Unless a sound theoretical background exists for selecting a particular distributi...
J. M. Muiño, Eberhard O. Voit, Albert Sorri...
NN
1998
Springer
177views Neural Networks» more  NN 1998»
15 years 6 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin