In high-SNR settings AJIVE's shared-subspace error is minimax-optimal and decays like 1/√K in the number of matrices, while in low-SNR settings a non-diminishing error floor appears even for an oracle-aided spectral estimator.
Detection limits in the high-dimensional spiked rectangular model
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Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices
In high-SNR settings AJIVE's shared-subspace error is minimax-optimal and decays like 1/√K in the number of matrices, while in low-SNR settings a non-diminishing error floor appears even for an oracle-aided spectral estimator.