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» An adaptive penalized maximum likelihood algorithm
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CORR
2007
Springer
128views Education» more  CORR 2007»
13 years 5 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'...
SIGMETRICS
2002
ACM
115views Hardware» more  SIGMETRICS 2002»
13 years 4 months ago
Maximum likelihood network topology identification from edge-based unicast measurements
Network tomography is a process for inferring "internal" link-level delay and loss performance information based on end-to-end (edge) network measurements. These methods...
Mark Coates, Rui Castro, Robert Nowak, Manik Gadhi...
JMLR
2012
11 years 7 months ago
Fast interior-point inference in high-dimensional sparse, penalized state-space models
We present an algorithm for fast posterior inference in penalized high-dimensional state-space models, suitable in the case where a few measurements are taken in each time step. W...
Eftychios A. Pnevmatikakis, Liam Paninski
ICC
2007
IEEE
150views Communications» more  ICC 2007»
13 years 11 months ago
Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems
— Blind and semiblind adaptive schemes are proposed for joint maximum likelihood (ML) channel estimation and data detection for multiple-input multiple-output (MIMO) systems. The...
Mohammed Abuthinien, Sheng Chen, Andreas Wolfgang,...
SIAMMAX
2010
145views more  SIAMMAX 2010»
13 years 43 min ago
Adaptive First-Order Methods for General Sparse Inverse Covariance Selection
In this paper, we consider estimating sparse inverse covariance of a Gaussian graphical model whose conditional independence is assumed to be partially known. Similarly as in [5],...
Zhaosong Lu