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low-precision computing 1matrix approximation 1performance optimization 1rank compensation 1tensor trains 1

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math.NA2026

Low-Precision Rank Compensation for Matrices and Tensor Trains

Ibrahim El Mountasser, Khalide Jbilou

The paper proposes reusing memory saved by low‑precision storage to increase the approximation rank of matrices and tensor‑train decompositions, showing that this rank compensation…