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We consider convex optimization problems formulated using dynamic programming equations. Such problems can be solved using the Dual Dynamic Programming algorithm combined with the Level 1 cut selection strategy or the Territory algorithm to…

Optimization and Control · Mathematics 2017-05-26 Vincent Guigues

This paper introduces the \emph{$d$-distance matching problem}, in which we are given a bipartite graph $G=(S,T;E)$ with $S=\{s_1,\dots,s_n\}$, a weight function on the edges and an integer $d\in\mathbb Z_+$. The goal is to find a maximum…

Combinatorics · Mathematics 2023-01-24 Péter Madarasi

In hypergraph theory, determining a characterization of the degree sequence $d=(d_1,d_2,\ldots,d_n)$ where $d_1\ge d_2\ge\ldots,d_n$ are positive integers, of an $h$-uniform simple hypergraph $\cal H$, and deciding the complexity status of…

Combinatorics · Mathematics 2013-10-01 A. Frosini , C. Picouleau , S. Rinaldi

All complete, axially symmetric surfaces of constant mean curvature in R^3 lie in the one-parameter family D_tau of Delaunay surfaces. The elements of this family which are embedded are called unduloids; all other elements, which correspond…

Differential Geometry · Mathematics 2007-05-23 Rafe Mazzeo , Frank Pacard

We define and study exact, efficient representations of realization spaces Euclidean Distance Constraint Systems (EDCS), which includes Linkages and Frameworks. Each representation corresponds to a choice of Cayley parameters and yields a…

Computational Geometry · Computer Science 2009-03-22 Meera Sitharam , Heping Gao

The group PGL(2) of linear transformations of the projective line acts naturally on the d-dimensional projective space P^d parametrizing configurations (`d-tuples') of points on the line. In this note we are concerned with the orbits of…

alg-geom · Mathematics 2012-04-10 Paolo Aluffi , Carel Faber

In this note we give a simple unifying proof of the undecidability of several diagrammatic properties of term rewriting systems that include: local confluence, strong confluence, diamond property, subcommutative property, and the existence…

Logic in Computer Science · Computer Science 2019-10-22 António Malheiro , Paulo Guilherme Santos

This paper is concerned with finite element error estimates for Neumann boundary control problems posed on convex and polyhedral domains. Different discretization concepts are considered and for each optimal discretization error estimates…

Numerical Analysis · Mathematics 2024-09-18 Johannes Pfefferer , Boris Vexler

In this paper we investigate the existence of subexponential parameterized algorithms of three fundamental cycle-hitting problems in geometric graph classes. The considered problems, \textsc{Triangle Hitting} (TH), \textsc{Feedback Vertex…

Data Structures and Algorithms · Computer Science 2024-04-17 Gaétan Berthe , Marin Bougeret , Daniel Gonçalves , Jean-Florent Raymond

We study the problem of robustly learning multi-dimensional histograms. A $d$-dimensional function $h: D \rightarrow \mathbb{R}$ is called a $k$-histogram if there exists a partition of the domain $D \subseteq \mathbb{R}^d$ into $k$…

Machine Learning · Computer Science 2018-02-26 Ilias Diakonikolas , Jerry Li , Ludwig Schmidt

Quadratization of polynomial and nonpolynomial systems of ordinary differential equations is advantageous in a variety of disciplines, such as systems theory, fluid mechanics, chemical reaction modeling and mathematical analysis. A…

Symbolic Computation · Computer Science 2023-12-07 Andrey Bychkov , Opal Issan , Gleb Pogudin , Boris Kramer

For a given digraph $D$ and distinct $u,v \in V(D)$, we denote by $\lambda_D(u,v)$ the local arc-connectivity from $u$ to $v$. Further, we define the total arc-connectivity $tac(D)$ of $D$ to be $\sum_{\{u,v\}\subseteq…

Combinatorics · Mathematics 2023-08-31 Florian Hörsch

Redundancy in deep neural network (DNN) models has always been one of their most intriguing and important properties. DNNs have been shown to overparameterize, or extract a lot of redundant features. In this work, we explore the impact of…

Machine Learning · Computer Science 2019-01-31 Babajide O. Ayinde , Tamer Inanc , Jacek M. Zurada

The Primal-Dual (PD) algorithm is widely used in convex optimization to determine saddle points. While the stability of the PD algorithm can be easily guaranteed, strict contraction is nontrivial to establish in most cases. This work…

Optimization and Control · Mathematics 2018-11-21 Hung D. Nguyen , Thanh Long Vu , Konstantin Turitsyn , Jean-Jacques Slotine

Motivated by quantum thermodynamics we first investigate the notion of strict positivity, that is, linear maps which map positive definite states to something positive definite again. We show that strict positivity is decided by the action…

Quantum Physics · Physics 2023-08-24 Frederik vom Ende

The matrix normed structure of the unitization of a (non-selfadjoint) operator algebra is determined by that of the original operator algebra. This yields a classification up to completely isometric isomorphism of two-dimensional unital…

funct-an · Mathematics 2007-05-23 Ralf Meyer

Two dimensional string theory is known to have an infinite dimensional symmetry, both in the continuum formalism as well as in the matrix model formalism. We develop a systematic procedure for computing the conserved charges associated with…

High Energy Physics - Theory · Physics 2009-09-15 Ashoke Sen

Let $P$ be a set of $n$ labeled points in the plane. The radial system of $P$ describes, for each $p\in P$, the order in which a ray that rotates around $p$ encounters the points in $P \setminus \{p\}$. This notion is related to the order…

Computational Geometry · Computer Science 2017-09-18 Oswin Aichholzer , Vincent Kusters , Wolfgang Mulzer , Alexander Pilz , Manuel Wettstein

We re-visit the complexity of kernelization for the $d$-Hitting Set problem. This is a classic problem in Parameterized Complexity, which encompasses several other of the most well-studied problems in this field, such as Vertex Cover,…

Data Structures and Algorithms · Computer Science 2023-08-14 Fedor V. Fomin , Tien-Nam Le , Daniel Lokshtanov , Saket Saurabh , Stephan Thomasse , Meirav Zehavi

A deep neural network (DNN) with piecewise linear activations can partition the input space into numerous small linear regions, where different linear functions are fitted. It is believed that the number of these regions represents the…

Machine Learning · Computer Science 2020-04-30 Xiao Zhang , Dongrui Wu