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Related papers: Modules in Robinson Spaces

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A Robinson space is a dissimilarity space $(X,d)$ on $n$ points for which there exists a compatible order, {\it i.e.} a total order $<$ on $X$ such that $x<y<z$ implies that $d(x,y)\le d(x,z)$ and $d(y,z)\leq d(x,z)$. Recognizing if a…

Discrete Mathematics · Computer Science 2023-06-16 Mikhael Carmona , Victor Chepoi , Guyslain Naves , Pascal Préa

Robinson spaces are structures equipped with a total order that encodes comparative dissimilarity relationships. We study the problem of representing Robinson dissimilarity spaces into low-dimensional metric spaces. These representations…

Combinatorics · Mathematics 2026-02-25 Francisco Arrepol , Mauricio Soto-Gomez , Christopher Thraves Caro

In this paper, we present a factor 16 approximation algorithm for the following NP-hard distance fitting problem: given a finite set X and a distance d on X, find a Robinsonian distance dR on X minimizing the l\infty-error ||d - dR||\infty…

Data Structures and Algorithms · Computer Science 2009-02-10 Victor Chepoi , M. Seston

In this work, we extend the concept of Robinson spaces to asymmetric dissimilarities, enhancing their applicability in representing and analyzing complex data. Within this generalized framework, we introduce two different problems that…

Discrete Mathematics · Computer Science 2024-12-06 Francois Brucker , Pascal Préa , Christopher Thraves Caro

A Robinson similarity matrix is a symmetric matrix where the entry values on all rows and columns increase toward the diagonal. Decompose the Robinson matrix into the sum of k {0, 1}-matrices, then these k {0, 1}-matrices are the adjacency…

Combinatorics · Mathematics 2021-05-20 Jeannette Janssen , Zhiyuan Zhang

This paper addresses two problems lying at the intersection of geometric analysis and theoretical computer science: The non-linear isomorphic Dvoretzky theorem and the design of good approximate distance oracles for large distortion. We…

Data Structures and Algorithms · Computer Science 2012-11-15 Manor Mendel , Assaf Naor

$\newcommand{\floor}[1]{\left\lfloor {#1} \right\rfloor} \renewcommand{\Re}{\mathbb{R}}$ Tverberg's theorem states that a set of $n$ points in $\Re^d$ can be partitioned into $\floor{n/(d+1)}$ sets with a common intersection. A point in…

Computational Geometry · Computer Science 2023-05-03 Sariel Har-Peled , Timothy Zhou

We study the space of all tilings which can be obtained using the Robinson tiles (this is a two-dimensional subshift of finite type). We prove that it has a unique minimal subshift, and describe it by means of a substitution. This…

Dynamical Systems · Mathematics 2012-03-08 Franz Gähler , Antoine Julien , Jean Savinien

A \textit{distinguishing partition} of a group $X$ with automorphism group ${aut}(X)$ is a partition of $X$ that is fixed by no nontrivial element of ${aut}(X)$. In the event that $X$ is a complete multipartite graph with its automorphism…

Combinatorics · Mathematics 2013-01-22 Michael Goff

Partitionings (or segmentations) divide a given domain into disjoint connected regions whose union forms again the entire domain. Multi-dimensional partitionings occur, for example, when analyzing parameter spaces of simulation models,…

Human-Computer Interaction · Computer Science 2024-10-28 Marina Evers , Lars Linsen

A metric space $\mathrm{M}=(M,\de)$ is {\em indivisible} if for every colouring $\chi: M\to 2$ there exists $i\in 2$ and a copy $\mathrm{N}=(N, \de)$ of $\mathrm{M}$ in $\mathrm{M}$ so that $\chi(x)=i$ for all $x\in N$. The metric space…

Combinatorics · Mathematics 2010-12-01 Norbert Sauer

An 'isomorphism' between the 'moduli space' of star products on $\R^2$ and the 'moduli space' of all formal Poisson structures on $\R^2$ is established.

q-alg · Mathematics 2008-02-03 Dmitry Tamarkin

We give a polynomial time algorithm to decode multivariate polynomial codes of degree $d$ up to half their minimum distance, when the evaluation points are an arbitrary product set $S^m$, for every $d < |S|$. Previously known algorithms can…

Computational Complexity · Computer Science 2015-11-25 John Kim , Swastik Kopparty

A differential module is a module equipped with a square-zero endomorphism. This structure underpins complexes of modules over rings, as well as differential graded modules over graded rings. We establish lower bounds on the class--a…

Commutative Algebra · Mathematics 2009-11-11 Luchezar L. Avramov , Ragnar-Olaf Buchweitz , Srikanth Iyengar

A $k$-regular partition into distinct parts is a partition into distinct parts with no part divisible by $k$. In this paper, we provide a general method to establish the unimodality of $k$-regular partition into distinct parts where the…

Combinatorics · Mathematics 2023-06-13 Janet J. W. Dong , Kathy Q. Ji

To every Poisson algebraic variety X over an algebraically closed field of characteristic zero, we canonically attach a right D-module M(X) on X. If X is affine, solutions of M(X) in the space of algebraic distributions on X are Poisson…

Symplectic Geometry · Mathematics 2010-12-24 Pavel Etingof , Travis Schedler , Ivan Losev

One fruitful formulation of Deep Networks (DNs) enabling their theoretical study and providing practical guidelines to practitioners relies on Piecewise Affine Splines. In that realm, a DN's input-mapping is expressed as per-region affine…

Machine Learning · Computer Science 2024-01-23 Randall Balestriero , Yann LeCun

A Lorentzian manifold is defined here as a smooth pseudo-Riemannian manifold with a metric tensor of signature ((2n +1, 1)). A Robinson manifold is a Lorentzian manifold (M) of dimension (\geqslant 4) with a subbundle (N) of the…

Differential Geometry · Mathematics 2007-05-23 Pawel Nurowski , Andrzej Trautman

A square symmetric matrix is a Robinson similarity matrix if entries in its rows and columns are non-decreasing when moving towards the diagonal. A Robinson similarity matrix can be viewed as the affinity matrix between objects arranged in…

Combinatorics · Mathematics 2024-06-26 Jeannette Janssen , Mahya Ghandehari

Although many machine learning algorithms involve learning subspaces with particular characteristics, optimizing a parameter matrix that is constrained to represent a subspace can be challenging. One solution is to use Riemannian…

Machine Learning · Computer Science 2017-03-10 Stephen Giguere , Francisco Garcia , Sridhar Mahadevan
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