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ICASSP
2011
IEEE
13 years 14 days 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
14 years 10 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»
13 years 10 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
13 years 10 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
14 years 2 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