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Let us assume that $f$ is a continuous function defined on the unit ball of $\mathbb R^d$, of the form $f(x) = g (A x)$, where $A$ is a $k \times d$ matrix and $g$ is a function of $k$ variables for $k \ll d$. We are given a budget $m \in…

Numerical Analysis · Mathematics 2012-01-18 Massimo Fornasier , Karin Schnass , Jan Vybiral

We describe an algorithm to compute the essentially different factorizations of a given image primitive integer-valued polynomial $f(X)=g(X)/d\in\Q[X]$, where $g\in\Z[X]$ and $d\in\N$ is square-free, assuming that the factorization of…

Commutative Algebra · Mathematics 2018-10-03 Giulio Peruginelli

Factorisation of integers $n$ is of number theoretic and cryptographic significance. The Number Field Sieve (NFS) introduced circa 1990, is still the state of the art algorithm, but no rigorous proof that it halts or generates relationships…

Number Theory · Mathematics 2018-05-24 Jonathan Lee , Ramarathnam Venkatesan

Nonnegative Matrix Factorization (NMF), first proposed in 1994 for data analysis, has received successively much attention in a great variety of contexts such as data mining, text clustering, computer vision, bioinformatics, etc. In this…

Numerical Analysis · Mathematics 2019-03-05 Paola Favati , Grazia Lotti , Ornella Menchi , Francesco Romani

Non-negative Matrix Factorization (NMF) asks to decompose a (entry-wise) non-negative matrix into the product of two smaller-sized nonnegative matrices, which has been shown intractable in general. In order to overcome this issue, the…

Data Structures and Algorithms · Computer Science 2019-07-15 Zhihuai Chen , Yinan Li , Xiaoming Sun , Pei Yuan , Jialin Zhang

We derive a tight upper bound on the probability over $\mathbf{x}=(x_1,\dots,x_\mu) \in \mathbb{Z}^\mu$ uniformly distributed in $ [0,m)^\mu$ that $f(\mathbf{x}) = 0 \bmod N$ for any $\mu$-linear polynomial $f \in…

Discrete Mathematics · Computer Science 2022-05-06 Benedikt Bünz , Ben Fisch

We introduce negative binomial matrix factorization (NBMF), a matrix factorization technique specially designed for analyzing over-dispersed count data. It can be viewed as an extension of Poisson matrix factorization (PF) perturbed by a…

Machine Learning · Computer Science 2018-01-08 Olivier Gouvert , Thomas Oberlin , Cédric Févotte

This work explores non-negative low-rank matrix factorization based on regularized Poisson models (PF or "Poisson factorization" for short) for recommender systems with implicit-feedback data. The properties of Poisson likelihood allow a…

Machine Learning · Computer Science 2022-02-25 David Cortes

Feature selection (FS) is assumed to improve predictive performance and identify meaningful features in high-dimensional datasets. Surprisingly, small random subsets of features (0.02-1%) match or outperform the predictive performance of…

Machine Learning · Computer Science 2025-09-22 Bhavesh Neekhra , Debayan Gupta , Partha Pratim Chakrabarti

Cyclotomic polynomials are basic objects in Number Theory. Their properties depend on the number of distinct primes that intervene in the factorization of their order, and the binary case is thus the first nontrivial case. This paper sees…

Number Theory · Mathematics 2024-11-07 Antonio Cafure , Eda Cesaratto

We obtain new lower bounds on the number of smooth squarefree integers up to $x$ in residue classes modulo a prime $p$, relatively large compared to $x$, which in some ranges of $p$ and $x$ improve that of A. Balog and C. Pomerance (1992).…

Number Theory · Mathematics 2019-03-11 Marc Munsch , Igor E. Shparlinski , Kam Hung Yau

We study representation of square-free polynomials in the polynomial ring F[t] over a finite field F by polynomials in F[t][x]. This is a function field version of the well-studied problem of representing squarefree integers by integer…

Number Theory · Mathematics 2013-07-16 Zeev Rudnick

Let $\Psi(x,y)$ denote the count of $y$-smooth numbers below $x$ and $P(n)$ denote the largest prime factor of $n$. We prove that for $f$ a Steinhaus random multiplicative function, the partial sums over $y$-smooth numbers always enjoy…

Number Theory · Mathematics 2026-02-09 Seth Hardy , Max Wenqiang Xu

In this paper we consider the problem of approximating function evaluations $f(\boldsymbol x_j)$ at given nonequispaced points $\boldsymbol x_j$, $j=1,\dots N$, of a bandlimited function from given values $\hat{f}(\boldsymbol k)$,…

Numerical Analysis · Mathematics 2025-04-17 Melanie Kircheis , Daniel Potts

As we all known, the nonnegative matrix factorization (NMF) is a dimension reduction method that has been widely used in image processing, text compressing and signal processing etc. In this paper, an algorithm for nonnegative matrix…

Numerical Analysis · Mathematics 2013-05-27 Shu-Zhen Lai , Hou-Biao Li , Zu-Tao Zhang

We get some results about the factorization of $\phi_p(M) \in {\mathbb{F}}_2[x]$, where $p$ is a prime number, $\phi_p$ is the corresponding cyclotomic polynomial and $M$ is a Mersenne prime (polynomial). By the way, we better understand…

Number Theory · Mathematics 2021-06-21 Luis H. Gallardo , Olivier Rahavandrainy

In this paper we study arithmetic computations in the nonassociative, and noncommutative free polynomial ring $\mathbb{F}\{x_1,x_2,\ldots,x_n\}$. Prior to this work, nonassociative arithmetic computation was considered by Hrubes, Wigderson,…

Computational Complexity · Computer Science 2017-07-07 V. Arvind , Rajit Datta , Partha Mukhopadhyay , S. Raja

Nonnegative matrix factorization (NMF) has been shown to be identifiable under the separability assumption, under which all the columns(or rows) of the input data matrix belong to the convex cone generated by only a few of these columns(or…

Machine Learning · Statistics 2014-03-25 Jason Gejie Liu , Shuchin Aeron

We study a function field version of a classical problem concerning square-free values of polynomials evaluated at primes. We show that for a square-free polynomial $f\in \mathbb{F}_q[t][x]$, there is a limiting density as $n\to \infty$ of…

Number Theory · Mathematics 2015-06-02 Guy Lando

Nonnegative matrix factorization (NMF) is a powerful tool for data mining. However, the emergence of `big data' has severely challenged our ability to compute this fundamental decomposition using deterministic algorithms. This paper…

Machine Learning · Statistics 2018-05-02 N. Benjamin Erichson , Ariana Mendible , Sophie Wihlborn , J. Nathan Kutz