A graph-based nearest-neighbor algorithm estimates sparse 3-tensors with small maximum entrywise error from p = n^{-3/2+κ} random observations per entry, nearly matching the conjectured efficient lower bound.
Noisy tensor completion via the sum-of-squares hierarchy
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Robust Max Entrywise Error Bounds for Tensor Estimation from Sparse Observations via Similarity Based Collaborative Filtering
A graph-based nearest-neighbor algorithm estimates sparse 3-tensors with small maximum entrywise error from p = n^{-3/2+κ} random observations per entry, nearly matching the conjectured efficient lower bound.