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Data-driven dimension selection in tensor regression commonly uses BIC-type criteria, cross-validation, or eigenvalue ratio methods; since the search space is the Cartesian product of the candidate dimensions of each mode, exhaustive search is costly, and common strategies are iterative per-mode selection or setting thresholds based on the eigenvalue spectrum.
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10/27/2026
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