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We discuss, in a non-Archimedean setting, the distribution of the coefficients of $L$-polynomials of curves of genus $g$ over $\mathbb{F}_q$. Among other results, this allows us to prove that the $\mathbb{Q}$-vector space spanned by such…

Number Theory · Mathematics 2025-07-25 Francesco Ballini , Davide Lombardo , Matteo Verzobio

We construct a sequence of rank 3 distributions on $n$-dimensional manifolds for any $n\geq 7$ such that the dimension of their symmetry group grows exponentially in $n$ (more precisely it is equal to $\operatorname{Fib}_{n-1}+n+2$, where…

Differential Geometry · Mathematics 2020-04-16 Boris Doubrov , Igor Zelenko

Scattered polynomials over finite fields attracted an increasing attention in the last years. One of the reasons is their deep connection with Maximum Rank Distance (MRD) codes. Known classification results for exceptional scattered…

Number Theory · Mathematics 2022-06-29 Daniele Bartoli , Massimo Giulietti , Giovanni Zini

The concept of scattered polynomials is generalized to those of exceptional scattered sequences which are shown to be the natural algebraic counterpart of $\mathbb{F}_{q^n}$-linear MRD codes. The first infinite family in the first…

Combinatorics · Mathematics 2022-11-22 Daniele Bartoli , Giuseppe Marino , Alessandro Neri , Lara Vicino

Kernel methods are an incredibly popular technique for extending linear models to non-linear problems via a mapping to an implicit, high-dimensional feature space. While kernel methods are computationally cheaper than an explicit feature…

Machine Learning · Statistics 2019-02-26 Philip Milton , Emanuele Giorgi , Samir Bhatt

We prove a number of results around kernelization of problems parameterized by the size of a given vertex cover of the input graph. We provide three sets of simple general conditions characterizing problems admitting kernels of polynomial…

Data Structures and Algorithms · Computer Science 2013-09-27 Fedor V. Fomin , Bart M. P. Jansen , Michal Pilipczuk

A kernel of a directed graph is a subset of vertices that is both independent and absorbing (every vertex not in the kernel has an out-neighbour in the kernel). Not all directed graphs contain kernels, and computing a kernel or deciding…

Discrete Mathematics · Computer Science 2024-05-20 Bruno Jartoux

Starting with a similarity function between objects, it is possible to define a distance metric on pairs of objects, and more generally on probability distributions over them. These distance metrics have a deep basis in functional analysis,…

Computational Geometry · Computer Science 2011-03-15 Sarang Joshi , Raj Varma Kommaraju , Jeff M. Phillips , Suresh Venkatasubramanian

Given a separable nonconstant polynomial $f(x)$ with integer coefficients, we consider the set $S$ consisting of the squarefree parts of all the rational values of $f(x)$, and study its behavior modulo primes. Fixing a prime $p$, we…

Number Theory · Mathematics 2014-07-21 David Krumm

The exploration of linear subspaces, particularly scattered subspaces, has garnered considerable attention across diverse mathematical disciplines in recent years, notably within finite geometries and coding theory. Scattered subspaces play…

Combinatorics · Mathematics 2024-05-16 Daniele Bartoli , Alessandro Giannoni , Giuseppe Marino

We show the existence of an exact mimicking network of $k^{O(\log k)}$ edges for minimum multicuts over a set of terminals in an undirected graph, where $k$ is the total capacity of the terminals, as well as a method for computing a…

Data Structures and Algorithms · Computer Science 2021-03-09 Magnus Wahlström

In this paper we present a high-order kernel method for numerically solving diffusion and reaction-diffusion partial differential equations (PDEs) on smooth, closed surfaces embedded in $\mathbb{R}^d$. For two-dimensional surfaces embedded…

Numerical Analysis · Mathematics 2012-06-04 Edward J. Fuselier , Grady B. Wright

The ranks and kernels of generalized Hadamard matrices are studied. It is proven that any generalized Hadamard matrix $H(q,\lambda)$ over $F_q$, $q>3$, or $q=3$ and $\gcd(3,\lambda)\not =1$, generates a self-orthogonal code. This result…

Information Theory · Computer Science 2016-11-15 Steven T. Dougherty , Josep Rifà , Mercè Villanueva

The kernel exponential family is a rich class of distributions, which can be fit efficiently and with statistical guarantees by score matching. Being required to choose a priori a simple kernel such as the Gaussian, however, limits its…

Machine Learning · Statistics 2021-01-15 Li Wenliang , Danica J. Sutherland , Heiko Strathmann , Arthur Gretton

Let $U$ be a set of polynomials of degree at most $k$ over $\mathbb{F}_q$, the finite field of $q$ elements. Assume that $U$ is an intersecting family, that is, the graphs of any two of the polynomials in $U$ share a common point.…

Combinatorics · Mathematics 2023-09-11 Angela Aguglia , Bence Csajbók , Zsuzsa Weiner

After a seminal paper by Shekeey (2016), a connection between maximum $h$-scattered $\mathbb{F}_q$-subspaces of $V(r,q^n)$ and maximum rank distance (MRD) codes has been established in the extremal cases $h=1$ and $h=r-1$. In this paper, we…

Combinatorics · Mathematics 2020-07-10 Giovanni Zini , Ferdinando Zullo

Intersecting codes are a classical object in coding theory whose rank-metric analogue has recently been introduced. Although the definition formally parallels the Hamming-metric case, the structure and parameter constraints of rank-metric…

Information Theory · Computer Science 2026-04-03 Martino Borello , Olga Polverino , Ferdinando Zullo

Fix an integer h>=1. In the universe of coloured trees of height at most h, we prove that for any graph decision problem defined by an MSO formula with r quantifiers, there exists a set of kernels, each of size bounded by an elementary…

Discrete Mathematics · Computer Science 2015-07-01 Jakub Gajarsky , Petr Hlineny

To determine the dimension of null space of any given linearized polynomial is one of vital problems in finite field theory, with concern to design of modern symmetric cryptosystems. But, the known general theory for this task is much far…

Information Theory · Computer Science 2018-11-29 Sihem Mesnager , Kwang Ho Kim , Myong Song Jo

Kernel mean embeddings have recently attracted the attention of the machine learning community. They map measures $\mu$ from some set $M$ to functions in a reproducing kernel Hilbert space (RKHS) with kernel $k$. The RKHS distance of two…

Machine Learning · Statistics 2019-12-18 Carl-Johann Simon-Gabriel , Bernhard Schölkopf