Compressed Covariance Estimation with Automated Dimension Learning

  title={Compressed Covariance Estimation with Automated Dimension Learning},
  author={Gautam S. Sabnis and Debdeep Pati and Anirban Bhattacharya},
  journal={Sankhya A},
We propose a method for estimating a covariance matrix that can be represented as a sum of a low-rank matrix and a diagonal matrix. The proposed method compresses high-dimensional data, computes the sample covariance in the compressed space, and lifts it back to the ambient space via a decompression operation. A salient feature of our approach relative to existing literature on combining sparsity and low-rank structures in covariance matrix estimation is that we do not require the low-rank… 


Sketching for simultaneously sparse and low-rank covariance matrices
  • S. Bahmani, J. Romberg
  • Computer Science, Mathematics
    2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
  • 2015
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