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ICASSP
2011
IEEE
14 years 6 months ago
Variational methods for spectral unmixing of hyperspectral images
This paper studies a variational Bayesian unmixing algorithm for hyperspectral images based on the standard linear mixing model. Each pixel of the image is modeled as a linear com...
Olivier Eches, Nicolas Dobigeon, Jean-Yves Tourner...
CVPR
2007
IEEE
16 years 4 months ago
Variational Bayes Based Approach to Robust Subspace Learning
This paper presents a new algorithm for the problem of robust subspace learning (RSL), i.e., the estimation of linear subspace parameters from a set of data points in the presence...
Takayuki Okatani, Koichiro Deguchi
ASPDAC
2007
ACM
98views Hardware» more  ASPDAC 2007»
15 years 4 months ago
A Software Technique to Improve Yield of Processor Chips in Presence of Ultra-Leaky SRAM Cells Caused by Process Variation
- Exceptionally leaky transistors are increasingly more frequent in nano-scale technologies due to lower threshold voltage and its increased variation. Such leaky transistors may e...
Maziar Goudarzi, Tohru Ishihara, Hiroto Yasuura
NIPS
2003
15 years 3 months ago
The IM Algorithm: A Variational Approach to Information Maximization
The maximisation of information transmission over noisy channels is a common, albeit generally computationally difficult problem. We approach the difficulty of computing the mutua...
David Barber, Felix V. Agakov
ICA
2004
Springer
15 years 7 months ago
Post-nonlinear Independent Component Analysis by Variational Bayesian Learning
Post-nonlinear (PNL) independent component analysis (ICA) is a generalisation of ICA where the observations are assumed to have been generated from independent sources by linear mi...
Alexander Ilin, Antti Honkela