• Corpus ID: 238226888

Causal Matrix Completion

@article{Agarwal2021CausalMC,
  title={Causal Matrix Completion},
  author={Anish Agarwal and Munther A. Dahleh and Devavrat Shah and Dennis Shen},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.15154}
}
Matrix completion is the study of recovering an underlying matrix from a sparse subset of noisy observations. Traditionally, it is assumed that the entries of the matrix are “missing completely at random” (MCAR), i.e., each entry is revealed at random, independent of everything else, with uniform probability. This is likely unrealistic due to the presence of “latent confounders”, i.e., unobserved factors that determine both the entries of the underlying matrix and the missingness pattern in the… 
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