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» Density Estimation by Mixture Models with Smoothing Priors
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SIAMSC
2011
219views more  SIAMSC 2011»
13 years 2 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...
ICIP
2000
IEEE
14 years 9 months ago
Normalized Training for HMM-Based Visual Speech Recognition
This paper presents an approach to estimating the parameters of continuous density HMMs for visual speech recognition. One of the key issues of image-based visual speech recogniti...
Yoshihiko Nankaku, Keiichi Tokuda, Tadashi Kitamur...
IDA
2009
Springer
14 years 2 days ago
Image Source Separation Using Color Channel Dependencies
We investigate the problem of source separation in images in the Bayesian framework using the color channel dependencies. As a case in point we consider the source separation of co...
Koray Kayabol, Ercan E. Kuruoglu, Bülent Sank...
VDA
2010
185views Visualization» more  VDA 2010»
13 years 10 months ago
Visualizing multidimensional data through granularity-dependent spatialization
Spatialization is a special kind of visualization that projects multidimensional data into low-dimensional representational spaces by making use of spatial metaphors. Spatializati...
Sofia Kontaxaki, Eleni Tomai, Margarita Kokla, Mar...
CDC
2008
IEEE
132views Control Systems» more  CDC 2008»
13 years 9 months ago
Global symplectic uncertainty propagation on SO(3)
Abstract-- This paper introduces a global uncertainty propagation scheme for the attitude dynamics of a rigid body, through a combination of numerical parametric uncertainty techni...
Taeyoung Lee, Melvin Leok, N. Harris McClamroch