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» An adaptive penalized maximum likelihood algorithm
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CORR
2007
Springer
128views Education» more  CORR 2007»
13 years 7 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 6 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 9 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»
14 years 1 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 1 months 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