primePCA iteratively imputes missing entries via projection onto current principal component estimates and updates the estimate with the leading right singular space, achieving geometric error convergence in the noiseless case under an incoherence condition when signal strength is sufficient.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
High-dimensional principal component analysis with heterogeneous missingness
primePCA iteratively imputes missing entries via projection onto current principal component estimates and updates the estimate with the leading right singular space, achieving geometric error convergence in the noiseless case under an incoherence condition when signal strength is sufficient.