"Our numerical studies suggest that the proposed CP-WOPT approach is accurate and scalable. CP-WOPT can recover the underlying factors successfully with large amounts of missing data, e.g., 90% missing entries for tensors of size 50 × 40 × 30. We have also studied how CP-WOPT can scale to problems of larger sizes, e.g., 1000 × 1000 × 1000, and recover CP factors from large, sparse tensors with 99.5% missing data.…"