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# Santiago Velazquez Iannuzzelli

Bio: Santiago Velazquez Iannuzzelli is an academic researcher. The author has contributed to research in topics: Mathematics & Similarity (geometry). The author has co-authored 4 publications.

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19 Oct 2022
TL;DR: In this paper , a generalization of the Fibonacci quilt sequence, the S -LID sequence, was proposed, which allows a n to be the smallest positive integer that cannot be expressed as a sum of non-adjacent previous terms.
Abstract: . Zeckendorf’s Theorem implies that the Fibonacci number F n is the smallest positive integer that cannot be written as a sum of non-consecutive previous Fibonacci numbers. Catral et al. studied a variation of the Fibonacci sequence, the Fibonacci Quilt sequence: the plane is tiled using the Fibonacci spiral, and integers are assigned to the squares of the spiral such that each square contains the smallest positive integer that cannot be expressed as the sum of non-adjacent previous terms. This adjacency is essentially captured in the diﬀerences of the indices of each square: the i th and j th squares are adjacent if and only if | i − j | ∈ { 1 , 3 , 4 } or { i, j } = { 1 , 3 } . We consider a generalization of this construction: given a set of positive integers S , the S -legal index diﬀerence ( S -LID) sequence ( a n ) ∞ n =1 is deﬁned by letting a n to be the smallest positive integer that cannot be written as P ℓ ∈ L a ℓ for some set L ⊂ [ n − 1] with | i − j | / ∈ S for all i, j ∈ L . We discuss our results governing the growth of S -LID sequences, as well as results proving that many families of sets S yield S -LID sequences which follow simple recurrence relations.
06 Oct 2022
TL;DR: In particular, the authors showed that a hypothesis class with finite VC-dimension is PAC-learnable under the assumption that the VC dimension of the hypothesis class is as large as possible.
Abstract: Given a domain $X$ and a collection $\mathcal{H}$ of functions $h:X\to \{0,1\}$, the Vapnik-Chervonenkis (VC) dimension of $\mathcal{H}$ measures its complexity in an appropriate sense. In particular, the fundamental theorem of statistical learning says that a hypothesis class with finite VC-dimension is PAC learnable. Recent work by Fitzpatrick, Wyman, the fourth and seventh named authors studied the VC-dimension of a natural family of functions $\mathcal{H}_t^{'2}(E): \mathbb{F}_q^2\to \{0,1\}$, corresponding to indicator functions of circles centered at points in a subset $E\subseteq \mathbb{F}_q^2$. They showed that when $|E|$ is large enough, the VC-dimension of $\mathcal{H}_t^{'2}(E)$ is the same as in the case that $E = \mathbb F_q^2$. We study a related hypothesis class, $\mathcal{H}_t^d(E)$, corresponding to intersections of spheres in $\mathbb{F}_q^d$, and ask how large $E\subseteq \mathbb{F}_q^d$ needs to be to ensure the maximum possible VC-dimension. We resolve this problem in all dimensions, proving that whenever $|E|\geq C_dq^{d-1/(d-1)}$ for $d\geq 3$, the VC-dimension of $\mathcal{H}_t^d(E)$ is as large as possible. We get a slightly stronger result if $d=3$: this result holds as long as $|E|\geq C_3 q^{7/3}$. Furthermore, when $d=2$ the result holds when $|E|\geq C_2 q^{7/4}$.
Journal ArticleDOI
TL;DR: In this paper , Fleischmann, Konyagin, Miller, Palsson, Pesikoff, and Wolf provide bounds on the minimum number of distinct angles in general position in three dimensions.
Abstract: In 1946, Erd\H{o}s posed the distinct distance problem, which seeks to find the minimum number of distinct distances between pairs of points selected from any configuration of $n$ points in the plane. The problem has since been explored along with many variants, including ones that extend it into higher dimensions. Less studied but no less intriguing is Erd\H{o}s' distinct angle problem, which seeks to find point configurations in the plane that minimize the number of distinct angles. In their recent paper "Distinct Angles in General Position," Fleischmann, Konyagin, Miller, Palsson, Pesikoff, and Wolf use a logarithmic spiral to establish an upper bound of $O(n^2)$ on the minimum number of distinct angles in the plane in general position, which prohibits three points on any line or four on any circle. We consider the question of distinct angles in three dimensions and provide bounds on the minimum number of distinct angles in general position in this setting. We focus on pinned variants of the question, and we examine explicit constructions of point configurations in $\mathbb{R}^3$ which use self-similarity to minimize the number of distinct angles. Furthermore, we study a variant of the distinct angles question regarding distinct angle chains and provide bounds on the minimum number of distinct chains in $\mathbb{R}^2$ and $\mathbb{R}^3$.
R G Ascoli
19 Jul 2023
TL;DR: In this article , the authors generalize Sun's result to arbitrary dimension and improve the exponent in the case $d=3, where the VC-dimension of the vector space is 3. Abstract: Let$\mathbb{F}_q^d$be the$d$-dimensional vector space over the finite field with$q$elements. For a subset$E\subseteq \mathbb{F}_q^d$and a fixed nonzero$t\in \mathbb{F}_q$, let$\mathcal{H}_t(E)=\{h_y: y\in E\}$, where$h_y$is the indicator function of the set$\{x\in E: x\cdot y=t\}$. Two of the authors, with Maxwell Sun, showed in the case$d=3$that if$|E|\geq Cq^{\frac{11}{4}}$and$q$is sufficiently large, then the VC-dimension of$\mathcal{H}_t(E)$is 3. In this paper, we generalize the result to arbitrary dimension and improve the exponent in the case$d=3\$.