Nov 7, 2009 · We prove that multilinear (tensor) analogues of many efficiently computable problems in numerical linear algebra are NP-hard.

Abstract. We prove that multilinear (tensor) analogues of many efficiently computable problems in numerical linear algebra are NP-hard.

We prove that multilinear (tensor) analogues of many efficiently computable problems in numerical linear algebra are NP-hard. Our list includes: determining ...

We show that tensor analogues of several standard problems that are readily computable in the matrix (i.e. 2-tensor) case are NP hard.

Dec 5, 2024 · We prove that multilinear (tensor) analogues of many efficiently computable problems in numerical linear algebra are NP-hard.

It is proved that multilinear (tensor) analogues of many efficiently computable problems in numerical linear algebra are NP-hard and how computing the ...

Jan 18, 2020 · In relation with this, I read that tensor rank is NP-complete (finite fields) or NP-hard (rationals). If P=NP could it still happen that ...

Aug 25, 2009 · For heavy tail phenomena, important to examine tensor-valued quantities like kurtosis. L.H. Lim (Berkeley). Most tensor problems are NP hard.

Oct 14, 2020 · Very informally, problem P1 polynomially reduces to P2 if there is a way to solve P1 by first solving P2 and then translating the ...

In this paper we prove that over most fields it is NP-hard to compute the rank of a tensor.