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» Robust estimation for sparse data
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CORR
2007
Springer
128views Education» more  CORR 2007»
14 years 9 months ago
Model Selection Through Sparse Maximum Likelihood Estimation
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
ICASSP
2008
IEEE
15 years 4 months ago
OFDM for underwater acoustic communications: Adaptive synchronization and sparse channel estimation
A phase synchronizationmethod, which provides non-uniform frequency offset compensation needed for wideband OFDM [1], is coupled with low-complexity channel estimation in the time...
Milica Stojanovic
KDD
2009
ACM
159views Data Mining» more  KDD 2009»
15 years 10 months ago
Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation
Effective diagnosis of Alzheimer's disease (AD), the most common type of dementia in elderly patients, is of primary importance in biomedical research. Recent studies have de...
Liang Sun, Rinkal Patel, Jun Liu, Kewei Chen, Tere...
CMSB
2004
Springer
15 years 1 months ago
Residual Bootstrapping and Median Filtering for Robust Estimation of Gene Networks from Microarray Data
We propose a robust estimation method of gene networks based on microarray gene expression data. It is well-known that microarray data contain a large amount of noise and some outl...
Seiya Imoto, Tomoyuki Higuchi, SunYong Kim, Euna J...
IBPRIA
2007
Springer
14 years 11 months ago
A Density-Based Data Reduction Algorithm for Robust Estimators
In this paper we present a non parametric density-based data reduction technique designed to be used in robust parameter estimation problems. Existing approaches are focused on red...
Luis Ferraz, Ramon Lluis Felip, Brais Martí...