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Linear constraints for a matrix polytope with no fractional vertex are investigated as intersecting research among permutation codes, rank modulations, and linear programming methods. By focusing the discussion to the block structure of…

Combinatorics · Mathematics 2012-02-07 Manabu Hagiwara

An important building block in all current asymptotically fast algorithms for matrix multiplication are tensors with low border rank, that is, tensors whose border rank is equal or very close to their size. To find new asymptotically fast…

Computational Complexity · Computer Science 2016-08-25 Markus Bläser , Vladimir Lysikov

Compressed sensing extends from the recovery of sparse vectors from undersampled measurements via efficient algorithms to the recovery of matrices of low rank from incomplete information. Here we consider a further extension to the…

Numerical Analysis · Mathematics 2014-11-04 Holger Rauhut , Reinhold Schneider , Zeljka Stojanac

We consider the problem of recovering a low-multilinear-rank tensor from a small amount of linear measurements. We show that the Riemannian gradient algorithm initialized by one step of iterative hard thresholding can reconstruct an…

Numerical Analysis · Mathematics 2021-01-14 Jian-Feng Cai , Lizhang Miao , Yang Wang , Yin Xian

Though algebraic geometry over $\mathbb C$ is often used to describe the closure of the tensors of a given size and complex rank, this variety includes tensors of both smaller and larger rank. Here we focus on the $n\times n\times n$…

Algebraic Geometry · Mathematics 2012-11-16 Elizabeth S. Allman , Peter D. Jarvis , John A. Rhodes , Jeremy G. Sumner

Low-rank tensor approximations have shown great potential for uncertainty quantification in high dimensions, for example, to build surrogate models that can be used to speed up large-scale inference problems (Eigel et al., Inverse Problems…

Numerical Analysis · Mathematics 2020-11-30 Paul B. Rohrbach , Sergey Dolgov , Lars Grasedyck , Robert Scheichl

Structures of multilinear maps are characterized by invariants. In this paper we introduce two invariants, named the isotropy index and the completeness index. These invariants capture the tensorial structure of the kernel of a multilinear…

Combinatorics · Mathematics 2025-11-03 Qiyuan Chen , Ke Ye

We consider the problem of learning low-rank tensors from partial observations with structural constraints, and propose a novel factorization of such tensors, which leads to a simpler optimization problem. The resulting problem is an…

Machine Learning · Computer Science 2023-05-16 Jayadev Naram , Tanmay Kumar Sinha , Pawan Kumar

We study tensor network varieties associated with the triangular graph, with a focus on the case where one of the physical dimensions is 2. This allows us to interpret the tensors as pencils of matrices. We provide a complete…

Algebraic Geometry · Mathematics 2026-02-18 Alessandra Bernardi , Fulvio Gesmundo

Tensors are often studied by introducing preorders such as restriction and degeneration: the former describes transformations of the tensors by local linear maps on its tensor factors; the latter describes transformations where the local…

Algebraic Geometry · Mathematics 2024-06-04 Matthias Christandl , Fulvio Gesmundo , Vladimir Lysikov , Vincent Steffan

We present three families of minimal border rank tensors: they come from highest weight vectors, smoothable algebras, or monomial algebras. We analyse them using Strassen's laser method and obtain an upper bound $2.431$ on $\omega$. We also…

Algebraic Geometry · Mathematics 2022-04-13 Roser Homs , Joachim Jelisiejew , Mateusz Michałek , Tim Seynnaeve

In this paper, we show that the low rank matrix completion problem can be reduced to the problem of finding the rank of a certain tensor.

Optimization and Control · Mathematics 2013-07-24 Harm Derksen

We prove new barrier results in arithmetic complexity theory, showing severe limitations of natural lifting (aka escalation) techniques. For example, we prove that even optimal rank lower bounds on $k$-tensors cannot yield non-trivial lower…

Computational Complexity · Computer Science 2019-04-10 Ankit Garg , Visu Makam , Rafael Oliveira , Avi Wigderson

Tensor parameters that are amortized or regularized over large tensor powers, often called "asymptotic" tensor parameters, play a central role in several areas including algebraic complexity theory (constructing fast matrix multiplication…

Computational Complexity · Computer Science 2025-09-11 Jop Briët , Matthias Christandl , Itai Leigh , Amir Shpilka , Jeroen Zuiddam

In this paper, the 3-rank of the incidence matrices of 2-designs supported by the minimum weight codewords in a family of ternary linear codes considered in [C. Ding, C. Li, Infinite families of 2-designs and 3-designs from linear codes,…

Information Theory · Computer Science 2019-07-31 Cunsheng Ding , Chunming Tang , Vladimir D. Tonchev

Unlike the matrix case, computing low-rank approximations of tensors is NP-hard and numerically ill-posed in general. Even the best rank-1 approximation of a tensor is NP-hard. In this paper, we use convex optimization to develop…

Statistics Theory · Mathematics 2016-09-14 Anil Aswani

We determine the border ranks of tensors that could potentially advance the known upper bound for the exponent $\omega$ of matrix multiplication. The Kronecker square of the small $q=2$ Coppersmith-Winograd tensor equals the $3\times 3$…

Algebraic Geometry · Mathematics 2020-09-25 Austin Conner , Hang Huang , J. M. Landsberg

The slice-rank method, introduced by Tao as a symmetrized version of the polynomial method of Croot, Lev and Pach and Ellenberg and Gijswijt, has proved to be a useful tool in a variety of combinatorial problems. Explicit tensors have been…

Combinatorics · Mathematics 2019-08-15 Simone Costa , Marco Dalai

We study the complexity of S-adic sequences corresponding to a family of 216 multi-dimensional continued fractions maps, called Triangle Partition maps (TRIP maps), with an emphasis on those with low upper bounds on complexity. Our main…

Dynamical Systems · Mathematics 2024-10-04 Thomas Garrity , Otto Vaughn Osterman

We make an in-depth study of the known border rank (i.e. approximate) algorithms for the matrix multiplication tensor encoding the multiplication of an n x 2 matrix by a 2 x 2 matrix.

Numerical Analysis · Computer Science 2015-09-29 J. M. Landsberg , Nicholas Ryder
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