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Cohn and Umans proposed a framework for developing fast matrix multiplication algorithms based on the embedding computation in certain groups algebras. In subsequent work with Kleinberg and Szegedy, they connected this to the search for…

Computational Complexity · Computer Science 2023-01-03 Matthew Anderson , Zongliang Ji , Anthony Yang Xu

We consider the matrix completion problem under a form of row/column weighted entrywise sampling, including the case of uniform entrywise sampling as a special case. We analyze the associated random observation operator, and prove that with…

Information Theory · Computer Science 2011-05-17 Sahand Negahban , Martin J. Wainwright

Given an increasing sequence of integers $x_1,\ldots,x_n$ from a universe $\{0,\ldots,u-1\}$, the monotone minimal perfect hash function (MMPHF) for this sequence is a data structure that answers the following rank queries: $rank(x) = i$ if…

Data Structures and Algorithms · Computer Science 2024-04-19 Dmitry Kosolobov

We prove that every infinite sequence of skew-symmetric or symmetric matrices M_1, M_2, ... over a fixed finite field must have a pair M_i, M_j (i<j) such that M_i is isomorphic to a principal submatrix of the Schur complement of a…

Combinatorics · Mathematics 2014-03-26 Sang-il Oum

This paper provides the best bounds to date on the number of randomly sampled entries required to reconstruct an unknown low rank matrix. These results improve on prior work by Candes and Recht, Candes and Tao, and Keshavan, Montanari, and…

Information Theory · Computer Science 2009-10-21 Benjamin Recht

We contribute towards resolving the open question of how many hidden layers are required in ReLU networks for exactly representing all continuous and piecewise linear functions on $\mathbb{R}^d$. While the question has been resolved in…

Machine Learning · Computer Science 2025-10-24 Moritz Grillo , Christoph Hertrich , Georg Loho

We give a self-contained proof of the strongest version of Mason's conjecture, namely that for any matroid the sequence of the number of independent sets of given sizes is ultra log-concave. To do this, we introduce a class of polynomials,…

Combinatorics · Mathematics 2018-11-06 Nima Anari , Kuikui Liu , Shayan Oveis Gharan , Cynthia Vinzant

We look at Bohemian matrices, specifically those with entries from $\{-1, 0, {+1}\}$. More, we specialize the matrices to be upper Hessenberg, with subdiagonal entries $\pm1$. Many properties remain after these specializations, some of…

Symbolic Computation · Computer Science 2018-09-28 Eunice Y. S. Chan , Robert M. Corless , Laureano Gonzalez-Vega , J. Rafael Sendra , Juana Sendra , Steven E. Thornton

We introduce the polynomial coefficient matrix and identify maximum rank of this matrix under variable substitution as a complexity measure for multivariate polynomials. We use our techniques to prove super-polynomial lower bounds against…

Computational Complexity · Computer Science 2013-02-15 Mrinal Kumar , Gaurav Maheshwari , Jayalal Sarma M. N

Let $R$ be the polydisc algebra or the Wiener algebra. It is shown that the group $SL_n(R)$ is generated by the subgroup of elementary matrices with all diagonal entries $1$ and at most one nonzero off-diagonal entry. The result an easy…

Commutative Algebra · Mathematics 2014-05-21 Amol Sasane

This work studies the expressivity of ReLU neural networks with a focus on their depth. A sequence of previous works showed that $\lceil \log_2(n+1) \rceil$ hidden layers are sufficient to compute all continuous piecewise linear (CPWL)…

Machine Learning · Computer Science 2026-02-23 Egor Bakaev , Florestan Brunck , Christoph Hertrich , Jack Stade , Amir Yehudayoff

We look at Bohemian matrices, specifically those with entries from $\{-1, 0, {+1}\}$. More, we specialize the matrices to be upper Hessenberg, with subdiagonal entries $1$. Even more, we consider Toeplitz matrices of this kind. Many…

Symbolic Computation · Computer Science 2018-10-01 Eunice Y. S. Chan , Robert M. Corless , Laureano Gonzalez-Vega , J. Rafael Sendra , Juana Sendra , Steven E. Thornton

This paper studies the minimal dimension required to embed subset memberships ($m$ elements and ${m\choose k}$ subsets of at most $k$ elements) into vector spaces, denoted as Minimal Embeddable Dimension (MED). The tight bounds of MED are…

Machine Learning · Computer Science 2026-01-30 Zihao Wang , Hang Yin , Lihui Liu , Hanghang Tong , Yangqiu Song , Ginny Wong , Simon See

We prove several limits on the behavior of a model of self-assembling particles introduced by Dabby and Chen (SODA 2013), called insertion systems, where monomers insert themselves into the middle of a growing linear polymer. First, we…

Data Structures and Algorithms · Computer Science 2015-10-29 Benjamin Hescott , Caleb Malchik , Andrew Winslow

A novel lower bound is introduced for the full rank probability of random finite field matrices, where a number of elements with known location are identically zero, and remaining elements are chosen independently of each other, uniformly…

Information Theory · Computer Science 2016-08-17 Daniel Salmond , Alex Grant , Ian Grivell , Terence Chan

We investigate the size of the largest entry (in absolute value) in the inverse of certain Vandermonde matrices. More precisely, for every real $b > 1$, let $M_b(n)$ be the maximum of the absolute values of the entries of the inverse of the…

Rings and Algebras · Mathematics 2020-08-04 Carlo Sanna , Jeffrey Shallit , Shun Zhang

The rigidity of a matrix describes the minimal number of entries one has to change to reduce matrix's rank to r. We give very simple combinatorial proof of the lower bound for the rigidity of Sylvester (special case of Hadamard) matrix that…

Computational Complexity · Computer Science 2007-05-23 Gatis Midrijanis

In this article, we investigate the $\operatorname{v}$-numbers of powers of monomial ideals and their integral closures in a polynomial ring $S$. We provide an alternative proof for determining the $\operatorname{v}$-numbers of powers of…

Commutative Algebra · Mathematics 2025-07-14 Vanmathi A , Parangama Sarkar

The Thompson-Higman groups G_{k,i} have a natural generalization to monoids M_{k,i}, and inverse monoids Inv_{k,i}. We study some structural features of M_{k,i} and Inv_{k,i} and investigate the computational complexity of decision…

Group Theory · Mathematics 2009-04-17 Jean-Camille Birget

We study two models of ReLU neural networks: monotone networks (ReLU$^+$) and input convex neural networks (ICNN). Our focus is on expressivity, mostly in terms of depth, and we prove the following lower bounds. For the maximum function…

Machine Learning · Computer Science 2025-05-12 Egor Bakaev , Florestan Brunck , Christoph Hertrich , Daniel Reichman , Amir Yehudayoff