A Note on Generalized Tensor CUR Approximation for Tensor Pairs and Tensor Triplets Based on the Tubal Product

In this note, we briefly present a generalized tensor CUR (GTCUR) approximation for tensor pairs (X̲,Y̲) and tensor triplets (X̲,Y̲,Z̲) based on the tubal product (t-product). We use the tensor Discrete Empirical Interpolation Method (TDEIM) to do these extensions. We demonstrate how the TDEIM can be applied to extend the traditional tensor CUR (TCUR) approximation, which operates on a single tensor, to simultaneously compute the TCUR approximations for two or three tensors. This method allows for the sampling of relevant lateral or horizontal slices from one data tensor in relation to one or two other data tensors. In certain special cases, the generalized TCUR (GTCUR) method simplifies to the classical TCUR approximations for both tensor pairs and tensor triplets, akin to the process shown for matrices. © Shanghai University 2025.

Авторы
Ahmadi-Asl Salman 1 , Rezaeian Naeim 2 , Ramazani Keivan 3
Издательство
Springer Nature
Язык
Английский
Статус
Опубликовано
Год
2026
Организации
  • 1 Lab of Machine Learning and Knowledge Representation, Innopolis University, Innopolis, Russian Federation
  • 2 RUDN University, Moscow, Moscow Oblast, Russian Federation
  • 3 Razi University, Kermanshah, Kermanshah, Iran
Ключевые слова
CUR approximation; Generalized tensor singular value decomposition (GTSVD); Tubal product (t-product)
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