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CORR
2010
Springer
210views Education» more  CORR 2010»
15 years 19 days ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad
ICA
2010
Springer
15 years 1 months ago
Recovering Spikes from Noisy Neuronal Calcium Signals via Structured Sparse Approximation
Two-photon calcium imaging is an emerging experimental technique that enables the study of information processing within neural circuits in vivo. While the spatial resolution of th...
Eva L. Dyer, Marco F. Duarte, Don H. Johnson, Rich...
87
Voted
BMCBI
2008
136views more  BMCBI 2008»
15 years 20 days ago
Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models
Background: When predictive survival models are built from high-dimensional data, there are often additional covariates, such as clinical scores, that by all means have to be incl...
Harald Binder, Martin Schumacher
108
Voted
ISSAC
2007
Springer
153views Mathematics» more  ISSAC 2007»
15 years 6 months ago
On exact and approximate interpolation of sparse rational functions
The black box algorithm for separating the numerator from the denominator of a multivariate rational function can be combined with sparse multivariate polynomial interpolation alg...
Erich Kaltofen, Zhengfeng Yang
101
Voted
ICCS
2003
Springer
15 years 5 months ago
Parallelisation of Sparse Grids for Large Scale Data Analysis
Sparse Grids are the basis for efficient high dimensional approximation and have recently been applied successfully to predictive modelling. They are spanned by a collection of si...
Jochen Garcke, Markus Hegland, Ole Møller N...