
Regularized tapered sample covariance matrix
Covariance matrix tapers have a long history in signal processing and re...
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On the variability of the sample covariance matrix under complex elliptical distributions
We derive the variancecovariance matrix of the sample covariance matrix...
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Coupled Feature Learning for Multimodal Medical Image Fusion
Multimodal image fusion aims to combine relevant information from images...
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Coupled regularized sample covariance matrix estimator for multiple classes
The estimation of covariance matrices of multiple classes with limited t...
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Blockwise MinimizationMajorization algorithm for Huber's criterion: sparse learning and applications
Huber's criterion can be used for robust joint estimation of regression ...
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Graph Signal Processing Meets Blind Source Separation
In graph signal processing (GSP), prior information on the dependencies ...
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Linear pooling of sample covariance matrices
We consider covariance matrix estimation in a setting, where there are m...
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Shrinking the eigenvalues of Mestimators of covariance matrix
A highly popular regularized (shrinkage) covariance matrix estimator is ...
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A Compressive Classification Framework for HighDimensional Data
We propose a compressive classification framework for settings where the...
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Mestimators of scatter with eigenvalue shrinkage
A popular regularized (shrinkage) covariance estimator is the shrinkage ...
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Modelling Graph Errors: Towards Robust Graph Signal Processing
The first step for any graph signal processing (GSP) procedure is to lea...
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Optimal shrinkage covariance matrix estimation under random sampling from elliptical distributions
This paper considers the problem of estimating a highdimensional (HD) c...
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Simultaneous Signal Subspace Rank and Model Selection with an Application to Singlesnapshot Source Localization
This paper proposes a novel method for model selection in linear regress...
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Sequential adaptive elastic net approach for singlesnapshot source localization
This paper proposes efficient algorithms for accurate recovery of direct...
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Compressive Regularized Discriminant Analysis of HighDimensional Data with Applications to Microarray Studies
We propose a modification of linear discriminant analysis, referred to a...
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Multichannel sparse recovery of complexvalued signals using Huber's criterion
In this paper, we generalize Huber's criterion to multichannel sparse re...
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Robust, scalable and fast bootstrap method for analyzing large scale data
In this paper we address the problem of performing statistical inference...
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Esa Ollila
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