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IGARSS
2009
13 years 7 months ago
Unmixing Sparse Hyperspectral Mixtures
Finding an accurate sparse approximation of a spectral vector described by a linear model, when there is available a library of possible constituent signals (called endmembers or ...
Marian-Daniel Iordache, José M. Bioucas-Dia...
ISBI
2006
IEEE
14 years 10 months ago
Early detection of rejection in cardiac MRI: a spectral graph approach
This paper develops an algorithm to detect abnormalities of small animals' transplanted hearts in MRI, at early stage of rejection when the hearts do not display prominent ab...
Chien Ho, Hsun-Hsien Chang, José M. F. Mour...
ASPDAC
2009
ACM
143views Hardware» more  ASPDAC 2009»
14 years 4 months ago
Statistical modeling and analysis of chip-level leakage power by spectral stochastic method
In this paper, we present a novel statistical full-chip leakage power analysis method. The new method can provide a general framework to derive the full-chip leakage current or po...
Ruijing Shen, Ning Mi, Sheldon X.-D. Tan, Yici Cai...
SIGGRAPH
1991
ACM
14 years 1 months ago
Spectrally optimal sampling for distribution ray tracing
Nonuniform sampling of images is a useful technique in computer graphics, because a properly designed pattern of samples can make aliasing take the form of high-frequency random n...
Don P. Mitchell
JMLR
2010
147views more  JMLR 2010»
13 years 4 months ago
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
Rahul Mazumder, Trevor Hastie, Robert Tibshirani