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BMCBI
2007
172views more  BMCBI 2007»
15 years 5 months ago
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks
Background: Reverse engineering cellular networks is currently one of the most challenging problems in systems biology. Dynamic Bayesian networks (DBNs) seem to be particularly su...
Fulvia Ferrazzi, Paola Sebastiani, Marco Ramoni, R...
TMI
2008
116views more  TMI 2008»
15 years 5 months ago
Reduced Encoding Diffusion Spectrum Imaging Implemented With a Bi-Gaussian Model
Diffusion spectrum imaging (DSI) can map complex fiber microstructures in tissues by characterizing their 3-D water diffusion spectra. However, a long acquisition time is required ...
Chun-Hung Yeh, Kuan-Hung Cho, Hsuan-Cheng Lin, Jiu...
JMLR
2010
158views more  JMLR 2010»
15 years 20 days ago
Restricted Eigenvalue Properties for Correlated Gaussian Designs
Methods based on 1-relaxation, such as basis pursuit and the Lasso, are very popular for sparse regression in high dimensions. The conditions for success of these methods are now ...
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
TSMC
2010
15 years 17 days ago
Binary Biometrics: An Analytic Framework to Estimate the Performance Curves Under Gaussian Assumption
In recent years the protection of biometric data has gained increased interest from the scientific community. Methods such as the fuzzy commitment scheme, helper data system, fuzzy...
Emile J. C. Kelkboom, Gary Garcia Molina, Jeroen B...
ICASSP
2010
IEEE
15 years 6 months ago
Algorithms for robust linear regression by exploiting the connection to sparse signal recovery
In this paper, we develop algorithms for robust linear regression by leveraging the connection between the problems of robust regression and sparse signal recovery. We explicitly ...
Yuzhe Jin, Bhaskar D. Rao