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BMCBI
2007
138views more  BMCBI 2007»
14 years 12 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...
103
Voted
EMMCVPR
2005
Springer
15 years 5 months ago
Segmentation Informed by Manifold Learning
In many biomedical imaging applications, video sequences are captured with low resolution and low contrast challenging conditions in which to detect, segment, or track features. Wh...
Qilong Zhang, Richard Souvenir, Robert Pless
ICDM
2008
IEEE
156views Data Mining» more  ICDM 2008»
15 years 6 months ago
Exploiting Local and Global Invariants for the Management of Large Scale Information Systems
This paper presents a data oriented approach to modeling the complex computing systems, in which an ensemble of correlation models are discovered to represent the system status. I...
Haifeng Chen, Haibin Cheng, Guofei Jiang, Kenji Yo...
ICANN
2003
Springer
15 years 5 months ago
Sparse Coding with Invariance Constraints
We suggest a new approach to optimize the learning of sparse features under the constraints of explicit transformation symmetries imposed on the set of feature vectors. Given a set...
Heiko Wersing, Julian Eggert, Edgar Körner
ICMLA
2007
15 years 1 months ago
Uncertainty optimization for robust dynamic optical flow estimation
We develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of ...
Volker Willert, Marc Toussaint, Julian Eggert, Edg...