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ICIP
2010
IEEE
15 years 4 months ago
Bayesian regularization of diffusion tensor images using hierarchical MCMC and loopy belief propagation
Based on the theory of Markov Random Fields, a Bayesian regularization model for diffusion tensor images (DTI) is proposed in this paper. The low-degree parameterization of diffus...
Siming Wei, Jing Hua, Jiajun Bu, Chun Chen, Yizhou...
ICCV
2009
IEEE
15 years 4 months ago
Kernel map compression using generalized radial basis functions
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Omar Arif, Patricio A. Vela
AI
2011
Springer
15 years 1 months ago
Representing preferences using intervals
In this paper we present a general framework for the comparison of intervals when preference relations have to established. The use of intervals in order to take into account impr...
Meltem Öztürk, Marc Pirlot, Alexis Tsouk...
CDC
2010
IEEE
15 years 1 months ago
Tuning a synthetic in vitro oscillator using control-theoretic tools
Abstract-- This paper demonstrates the effectiveness of simple control-theoretic tools in generating simulation-guided experiments on a synthetic in vitro oscillator. A theoretical...
Christopher Sturk, Elisa Franco, Richard M. Murray
226
Voted
TSP
2010
15 years 1 months ago
Methods for sparse signal recovery using Kalman filtering with embedded pseudo-measurement norms and quasi-norms
We present two simple methods for recovering sparse signals from a series of noisy observations. The theory of compressed sensing (CS) requires solving a convex constrained minimiz...
Avishy Carmi, Pini Gurfil, Dimitri Kanevsky