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» Adaptive Sampling for Noisy Problems
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TMI
2010
175views more  TMI 2010»
13 years 2 months ago
Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Thomas Vincent, Laurent Risser, Philippe Ciuciu
BMCBI
2011
12 years 11 months ago
To aggregate or not to aggregate high-dimensional classifiers
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
Cheng-Jian Xu, Huub C. J. Hoefsloot, Age K. Smilde
COMPLIFE
2006
Springer
13 years 11 months ago
Beating the Noise: New Statistical Methods for Detecting Signals in MALDI-TOF Spectra Below Noise Level
Background: The computer-assisted detection of small molecules by mass spectrometry in biological samples provides a snapshot of thousands of peptides, protein fragments and prote...
Tim O. F. Conrad, Alexander Leichtle, Andre Hageh&...
BMCBI
2006
116views more  BMCBI 2006»
13 years 7 months ago
Integrative missing value estimation for microarray data
Background: Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performan...
Jianjun Hu, Haifeng Li, Michael S. Waterman, Xiang...
3DIM
2005
IEEE
13 years 9 months ago
Bayesian Modelling of Camera Calibration and Reconstruction
Camera calibration methods, whether implicit or explicit, are a critical part of most 3D vision systems. These methods involve estimation of a model for the camera that produced t...
Rashmi Sundareswara, Paul R. Schrater