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» Selection in the Presence of Noise
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TSP
2010
14 years 4 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
BMCBI
2010
140views more  BMCBI 2010»
14 years 10 months ago
Quantification and deconvolution of asymmetric LC-MS peaks using the bi-Gaussian mixture model and statistical model selection
Background: Liquid chromatography-mass spectrometry (LC-MS) is one of the major techniques for the quantification of metabolites in complex biological samples. Peak modeling is on...
Tianwei Yu, Hesen Peng
INFOCOM
2012
IEEE
13 years 9 days ago
Robust multi-source network tomography using selective probes
—Knowledge of a network’s topology and internal characteristics such as delay times or losses is crucial to maintain seamless operation of network services. Network tomography ...
Akshay Krishnamurthy, Aarti Singh
CORR
2010
Springer
139views Education» more  CORR 2010»
14 years 4 months ago
On Communication over Unknown Sparse Frequency-Selective Block-Fading Channels
The problem of reliable communication over unknown frequency-selective block-fading channels with sparse impulse responses is considered. In particular, discrete-time impulse respo...
Arun Pachai Kannu, Philip Schniter
CSDA
2007
152views more  CSDA 2007»
14 years 9 months ago
Robust variable selection using least angle regression and elemental set sampling
In this paper we address the problem of selecting variables or features in a regression model in the presence of both additive (vertical) and leverage outliers. Since variable sel...
Lauren McCann, Roy E. Welsch