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For every $n \in \mathbb{N}$ and every field $K$, let $A(n,K)$ be the vector space of the antisymmetric $(n \times n)$-matrices over $K$. We say that an affine subspace $S$ of $A(n,K)$ has constant rank $r$ if every matrix of $S$ has rank…

Rings and Algebras · Mathematics 2024-12-03 Elena Rubei

If $f$ is a symmetric complex-valued function on the $m$-fold Cartesian product of the set of non-negative reals and $A$ is a positive semi-definite $m\times m$ matrix with eigenvalues $\lambda_j$, we set…

Functional Analysis · Mathematics 2016-12-13 Lutz Klotz , Conrad Mädler

Nonnegative matrix factorization (NMF) has become a very popular technique in machine learning because it automatically extracts meaningful features through a sparse and part-based representation. However, NMF has the drawback of being…

Machine Learning · Statistics 2012-12-07 Nicolas Gillis

An interval matrix is a matrix whose entries are intervals in the set of real numbers. Let $p , q $ be nonzero natural numbers and let $\mu =( [m_{i,j}, M_{i,j}])_{i,j}$ be a $p \times q$ interval matrix; given a $p \times q$ matrix $A$…

Rings and Algebras · Mathematics 2018-03-02 Elena Rubei

We study relationships between permutation statistics and pattern-functions, counting the number of times particular patterns occur in a permutation. This allows us to write several familiar statistics as linear combinations of pattern…

Combinatorics · Mathematics 2022-11-22 Yosef Berman , Bridget Eileen Tenner

Denote by $A_n$ the set of square $(0,1)$ matrices of order $n$. The set $A_n$, $n\le8$, is partitioned into row/column permutation equivalence classes enabling derivation of various facts by simple counting. For example, the number of…

Combinatorics · Mathematics 2007-05-23 Miodrag Živković

This work demonstrates a methodology for using deep learning to discover simple, practical criteria for classifying matrices based on abstract algebraic properties. By combining a high-performance neural network with explainable AI (XAI)…

Machine Learning · Computer Science 2025-07-31 Leandro Farina , Sergey Korotov

CMF is a technique for simultaneously learning low-rank representations based on a collection of matrices with shared entities. A typical example is the joint modeling of user-item, item-property, and user-feature matrices in a recommender…

Machine Learning · Statistics 2014-11-19 Arto Klami , Guillaume Bouchard , Abhishek Tripathi

This paper considers a restriction to non-negative matrix factorization in which at least one matrix factor is stochastic. That is, the elements of the matrix factors are non-negative and the columns of one matrix factor sum to 1. This…

Machine Learning · Statistics 2016-09-20 Christopher Adams

We propose a novel scheme that allows MIMO system to modulate a set of permutation matrices to send more information bits, extending our initial work on the topic. This system is called Permutation Matrix Modulation (PMM). The basic idea is…

Information Theory · Computer Science 2022-12-27 Rahmat Faddli Siregar , Nandana Rajatheva , Matti Latva-Aho

Given a linear system $\dot{x} = Ax$, where $A$ is an $n \times n$ matrix with $m$ nonzero entries, we consider the problem of finding the smallest set of state variables to affect with an input so that the resulting system is structurally…

Optimization and Control · Mathematics 2014-09-30 Alex Olshevsky

Matrix completion tackles the task of predicting missing values in a low-rank matrix based on a sparse set of observed entries. It is often assumed that the observation pattern is generated uniformly at random or has a very specific…

Machine Learning · Statistics 2025-03-18 Yudong Chen , Xumei Xi , Christina Lee Yu

Sparse matrix factorization is the problem of approximating a matrix $\mathbf{Z}$ by a product of $J$ sparse factors $\mathbf{X}^{(J)} \mathbf{X}^{(J-1)} \ldots \mathbf{X}^{(1)}$. This paper focuses on identifiability issues that appear in…

Machine Learning · Computer Science 2021-11-18 Léon Zheng , Elisa Riccietti , Rémi Gribonval

In this paper we relate t-designs to a forbidden configuration problem in extremal set theory. Let 1_t 0_l denote a column of t 1's on top of l 0's. We assume t>l. Let q. (1_t 0_l) denote the (t+l)xq matrix consisting of t rows of q 1's and…

Combinatorics · Mathematics 2019-09-26 R. P. Anstee , Farzin Barekat , Zachary Pellegrin

Given a matrix with partitions of its rows and columns and entries from a field, we give the necessary and sufficient conditions that it has a non--singular submatrix with certain number of rows from each row partition and certain number of…

Combinatorics · Mathematics 2009-08-04 S. M. Sadegh Tabatabaei Yazdi , Serap A. Savari

We give the first algorithm for Matrix Completion whose running time and sample complexity is polynomial in the rank of the unknown target matrix, linear in the dimension of the matrix, and logarithmic in the condition number of the matrix.…

Machine Learning · Computer Science 2014-07-16 Moritz Hardt , Mary Wootters

We consider Conditional Random Fields (CRFs) with pattern-based potentials defined on a chain. In this model the energy of a string (labeling) $x_1...x_n$ is the sum of terms over intervals $[i,j]$ where each term is non-zero only if the…

Machine Learning · Computer Science 2017-01-23 Rustem Takhanov , Vladimir Kolmogorov

Let $m,n\ge 2$ be integers. Denote by $M_n$ the set of $n\times n$ complex matrices. Let $\|\cdot\|_{(p,k)}$ be the $(p,k)$ norm on $M_{mn}$ with $1\leq k\leq mn$ and $2<p<\infty$. We show that a linear map $\phi:M_{mn}\rightarrow M_{mn}$…

Functional Analysis · Mathematics 2023-08-24 Zejun Huang , Nung-Sing Sze , Run Zheng

Let M be a random (alpha n) x n matrix of rank r<<n, and assume that a uniformly random subset E of its entries is observed. We describe an efficient algorithm that reconstructs M from |E| = O(rn) observed entries with relative root mean…

Machine Learning · Computer Science 2009-09-17 Raghunandan H. Keshavan , Andrea Montanari , Sewoong Oh

In this paper a novel approach for matrix manipulation and indexing is proposed .Here the elements in a row of matrix are designated by numeric value called permutation index followed by the elements of the row being randomised. This is…

Cryptography and Security · Computer Science 2013-12-17 Rahul R Upadhyay