A Normal Form Algorithm for Tensor Rank Decomposition

• Published in: ACM transactions on mathematical software Vol. 48; no. 4; pp. 1 - 35
• Main Authors: Telen, Simon, Vannieuwenhoven, Nick
• Format: Journal Article
• Language: English
• Published: New York, NY ACM 19.12.2022
• Subjects: Computations on matrices; Computations on polynomials; Mathematics of computing; Nonlinear equations; Solvers; canonical polyadic decomposition; polynomial systems; Tensor rank decomposition; normal form algorithms
• ISSN: 0098-3500; 1557-7295; 1557-7295
• DOI: 10.1145/3555369

We propose a new numerical algorithm for computing the tensor rank decomposition or canonical polyadic decomposition of higher-order tensors subject to a rank and genericity constraint. Reformulating this computational problem as a system of polynomial equations allows us to leverage recent numerical linear algebra tools from computational algebraic geometry. We characterize the complexity of our algorithm in terms of an algebraic property of this polynomial system—the multigraded regularity. We prove effective bounds for many tensor formats and ranks, which are of independent interest for overconstrained polynomial system solving. Moreover, we conjecture a general formula for the multigraded regularity, yielding a (parameterized) polynomial time complexity for the tensor rank decomposition problem in the considered setting. Our numerical experiments show that our algorithm can outperform state-of-the-art numerical algorithms by an order of magnitude in terms of accuracy, computation time, and memory consumption.