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Joint Covariance Estimation With Mutual Linear Structure
Ilya Soloveychik
,
Ami Wiesel
The Rachel and Selim Benin School of Engineering and Computer Science
Research output
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Contribution to journal
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Article
›
peer-review
2
Scopus citations
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Dive into the research topics of 'Joint Covariance Estimation With Mutual Linear Structure'. Together they form a unique fingerprint.
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Keyphrases
Covariance
100%
Covariance Estimation
100%
Linear Structure
100%
Numerical Simulation
50%
Joint Estimation
50%
Symmetric Matrices
50%
Performance Benefits
50%
Training Set
50%
Principal Coordinate Analysis (PCoA)
50%
Matrix Spaces
50%
Covariance Matrix
50%
Mutual Structure
50%
Heterogeneous Training
50%
Structured Covariance Matrix
50%
Performance Bounds
50%
Cramér-Rao Lower Bound
50%
Affine Subspace
50%
Mathematics
Covariance
100%
Linear Structure
100%
Covariance Matrix
66%
Matrix (Mathematics)
33%
Gaussian Distribution
33%
Symmetric Matrix
33%
Training Set
33%
Affine Subspace
33%
Computer Simulation
33%
Principal Component Analysis
33%