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Let $d\ge 1$ be an integer and ${\bf r}=(r_0,\dots,r_{d-1}) \in \mathbf{R}^d$. The {\em shift radix system} $\tau_\mathbf{r}: \mathbb{Z}^d \to \mathbb{Z}^d$ is defined by $$ \tau_{{\bf r}}({\bf z})=(z_1,\dots,z_{d-1},-\lfloor {\bf r} {\bf…

Number Theory · Mathematics 2015-01-23 Peter Kirschenhofer , Jörg M. Thuswaldner

The vertices of a finite state system are usually a subset of the natural numbers. Most algorithms relative to these systems only use this fact to select vertices. For infinite state systems, however, the situation is different: in…

Formal Languages and Automata Theory · Computer Science 2009-11-18 Christophe Morvan

There are two-dimensional expanding shift radix systems (SRS) which have some periodic orbits. The aim of the present paper is to describe such unusual points as well as possible. We give all regions that contain parameters the…

Number Theory · Mathematics 2019-10-04 Attila Pethő , Jörg Thuswaldner , Mario Weitzer

Let $A$ be an $n \times n$ matrix with rational entries and let \[ \mathbb{Z}^n[A] := \bigcup_{k=1}^{\infty} \left( \mathbb{Z}^n + A\mathbb{Z}^n + \dots + A^{k-1}\mathbb{Z}^n\right) \] be the minimal $A$-invariant $\mathbb{Z}$-module…

Number Theory · Mathematics 2018-08-03 Jonas Jankauskas , Jörg Thuswaldner

The stability and convergence analysis of high-order numerical approximations for the one- and two-dimensional nonlocal wave equations on unbounded spatial domains are considered. We first use the quadrature-based finite difference schemes…

Numerical Analysis · Mathematics 2022-11-09 Jihong Wang , Jerry Zhijian Yang , Jiwei Zhang

Recently, interesting empirical phenomena known as Neural Collapse have been observed during the final phase of training deep neural networks for classification tasks. We examine this issue when the feature dimension d is equal to the…

Machine Learning · Computer Science 2024-07-23 Yi Shen , Shao Gu

Previous work has shown that DNNs with large depth $L$ and $L_{2}$-regularization are biased towards learning low-dimensional representations of the inputs, which can be interpreted as minimizing a notion of rank $R^{(0)}(f)$ of the learned…

Machine Learning · Computer Science 2024-08-16 Arthur Jacot

High-order methods for convex and nonconvex optimization, particularly $p$th-order Adaptive Regularization Methods (AR$p$), have attracted significant research interest by naturally incorporating high-order Taylor models into adaptive…

Optimization and Control · Mathematics 2025-04-30 Wenqi Zhu , Coralia Cartis

We analyze integer linear programs which we obtain after discretizing two-dimensional subproblems arising from a trust-region algorithm for mixed integer optimal control problems with total variation regularization. We discuss NP-hardness…

Optimization and Control · Mathematics 2025-03-07 Paul Manns , Marvin Severitt

In the Dominated Cluster Deletion problem, we are given an undirected graph $G$ and integers $k$ and $d$ and the question is to decide whether there exists a set of at most $k$ vertices whose removal results in a graph in which each…

Discrete Mathematics · Computer Science 2025-08-20 Nicole Schirrmacher , Sebastian Siebertz , Alexandre Vigny

We consider a family of deep neural networks consisting of two groups of convolutional layers, a downsampling operator, and a fully connected layer. The network structure depends on two structural parameters which determine the numbers of…

Machine Learning · Computer Science 2021-07-05 Tong Mao , Zhongjie Shi , Ding-Xuan Zhou

In this paper we propose a procedure which allows the construction of a large family of FIR d x d matrix wavelet filters by exploiting the one-to-one correspondence between QMF systems and orthogonal operators which commute with the shifts…

Numerical Analysis · Mathematics 2013-03-06 Mariantonia Cotronei , Matthias Holschneider

These are some informal remarks on quadratic orbital networks over finite fields. We discuss connectivity, Euler characteristic, number of cliques, planarity, diameter and inductive dimension. We find a non-trivial disconnected graph for…

Dynamical Systems · Mathematics 2013-12-03 Oliver Knill

The theory of the tight span, a cell complex that can be associated to every metric $D$, offers a unifying view on existing approaches for analyzing distance data, in particular for decomposing a metric $D$ into a sum of simpler metrics as…

Data Structures and Algorithms · Computer Science 2009-10-14 A. Dress , K. T. Huber , J. Koolen , V. Moulton , A. Spillner

DR-submodular continuous functions are important objectives with wide real-world applications spanning MAP inference in determinantal point processes (DPPs), and mean-field inference for probabilistic submodular models, amongst others.…

Machine Learning · Computer Science 2019-05-27 An Bian , Kfir Y. Levy , Andreas Krause , Joachim M. Buhmann

Let $X\subset A^{Z^d}$ be a $2$-dimensional subshift of finite type. We prove that any $2$-dimensional multidimensional subshift of finite type can be characterized by a square matrix of infinite dimension. We extend our result to a general…

Dynamical Systems · Mathematics 2016-03-03 Puneet Sharma , Dileep Kumar

Let $\RR$ be a real closed field (e.g. the field of real numbers) and $\mathscr{S} \subset \RR^n$ be a semi-algebraic set defined as the set of points in $\RR^n$ satisfying a system of $s$ equalities and inequalities of multivariate…

Symbolic Computation · Computer Science 2013-09-20 Mohab Safey El Din , Elias Tsigaridas

Let $A$ be a $d \times d$ matrix with rational entries which has no eigenvalue $\lambda \in \mathbb{C}$ of absolute value $|\lambda| < 1$ and let $\mathbb{Z}^d[A]$ be the smallest nontrivial $A$-invariant $\mathbb{Z}$-module. We lay down a…

Number Theory · Mathematics 2021-12-10 Jonas Jankauskas , Jörg M. Thuswaldner

A Lagrange Theorem in dimension 2 is proved, for a particular two-dimensional algorithm, with a very natural geometrical definition. Dirichlet-type properties for the convergence of the algorithm are also proved. These properties procced…

Number Theory · Mathematics 2015-02-17 Christian Drouin

We propose and investigate a new algorithm for quantifying the topological properties of cosmological density fluctuations. We first motivate this algorithm by drawing a formal distinction between two definitions of relevant topological…

Astrophysics · Physics 2015-06-24 Peter Coles , Andrew G. Davies , Russell C. Pearson
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