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A multiplicative $\alpha$-spanner $H$ is a subgraph of $G=(V,E)$ with the same vertices and fewer edges that preserves distances up to the factor $\alpha$, i.e., $d_H(u,v)\leq\alpha\cdot d_G(u,v)$ for all vertices $u$, $v$. While many…

Data Structures and Algorithms · Computer Science 2021-07-06 Markus Chimani , Finn Stutzenstein

Spatially-sparse predictors are good models for brain decoding: they give accurate predictions and their weight maps are interpretable as they focus on a small number of regions. However, the state of the art, based on total variation or…

Machine Learning · Statistics 2016-06-22 Gaël Varoquaux , Matthieu Kowalski , Bertrand Thirion

A graph is locally irregular if any pair of adjacent vertices have distinct degrees. A locally irregular decomposition of a graph $G$ is a decomposition $\mathcal{D}$ of $G$ such that every subgraph $H \in \mathcal{D}$ is locally irregular.…

Combinatorics · Mathematics 2019-02-05 Carla Negri Lintzmayer , Guilherme Oliveira Mota , Maycon Sambinelli

We propose a real-space approach explaining and controlling the occurrence of edge-localized gap states between the spectral quasibands of binary tight binding chains with deterministic aperiodic long-range order. The framework is applied…

Mesoscale and Nanoscale Physics · Physics 2019-06-12 Malte Röntgen , Christian V. Morfonios , Ren Wang , Luca Dal Negro , Peter Schmelcher

Let $G$ be a connected reductive group acting on an irreducible normal algebraic variety $X$. We give a slightly improved version of local structure theorems obtained by F.Knop and D.A.Timashev that describe an action of some parabolic…

Algebraic Geometry · Mathematics 2011-09-16 Vladimir S. Zhgoon

The study of the optimality of low-complexity greedy scheduling techniques in wireless communications networks is a very complex problem. The Local Pooling (LoP) factor provides a single-parameter means of expressing the achievable capacity…

Information Theory · Computer Science 2015-08-04 Jeffrey Wildman , Steven Weber

We propose a novel semi-supervised structured output prediction method based on local linear regression in this paper. The existing semi-supervise structured output prediction methods learn a global predictor for all the data points in a…

Machine Learning · Computer Science 2016-08-17 Ru-Ze Liang , Wei Xie , Weizhi Li , Xin Du , Jim Jing-Yan Wang , Jingbin Wang

A temporal graph is an undirected graph $G=(V,E)$ along with a function that assigns a time-label to each edge in $E$. A path in $G$ with non-decreasing time-labels is called temporal path and the distance from $u$ to $v$ is the minimum…

Data Structures and Algorithms · Computer Science 2022-06-23 Davide Bilò , Gianlorenzo D'Angelo , Luciano Gualà , Stefano Leucci , Mirko Rossi

An \emph{additive +$\beta W$ spanner} of an edge weighted graph $G=(V,E)$ is a subgraph $H$ of $G$ such that for every pair of vertices $u$ and $v$, $d_{H}(u,v) \le d_G(u,v) + \beta W$, where $d_G(u,v)$ is the shortest path length from $u$…

Data Structures and Algorithms · Computer Science 2025-02-18 Reyan Ahmed , Debajyoti Mondal , Rahnuma Islam Nishat

Local robustness ensures that a model classifies all inputs within an $\ell_2$-ball consistently, which precludes various forms of adversarial inputs. In this paper, we present a fast procedure for checking local robustness in feed-forward…

Machine Learning · Computer Science 2021-02-19 Aymeric Fromherz , Klas Leino , Matt Fredrikson , Bryan Parno , Corina Păsăreanu

$\renewcommand{\Re}{\mathbb{R}}$Recent work showed how to construct nearest-neighbor graphs of linear size, on a given set $P$ of $n$ points in $\Re^d$, such that one can answer approximate nearest-neighbor queries in logarithmic time in…

Computational Geometry · Computer Science 2026-02-10 Jeff Giliberti , Sariel Har-Peled , Jonas Sauer , Ali Vakilian

Kim defined a very general combinatorial abstraction of the diameter of polytopes called subset partition graphs to study how certain combinatorial properties of such graphs may be achieved in lower bound constructions. Using Lov\'asz'…

Combinatorics · Mathematics 2012-03-08 Nicolai Hähnle

Given a finite set $E$, a subset $D\sub E$ (viewed as a function $E\to \F_2$) is orthogonal to a given subspace $\FF$ of the $\F_2$-vector space of functions $E\to \F_2$ as soon as $D$ is orthogonal to every $\sub$-minimal element of $\FF$.…

Combinatorics · Mathematics 2013-08-14 Reinhard Diestel , Julian Pott

Highly connected and yet sparse graphs (such as expanders or graphs of high treewidth) are fundamental, widely applicable and extensively studied combinatorial objects. We initiate the study of such highly connected graphs that are, in…

Computational Geometry · Computer Science 2013-06-17 Prosenjit Bose , Vida Dujmovic , Pat Morin , Michiel Smid

Over-squashing is a challenge in training graph neural networks for tasks involving long-range dependencies. In such tasks, a GNN's receptive field should be large enough to enable communication between distant nodes. However, gathering…

Machine Learning · Computer Science 2025-08-29 Tuğrul Hasan Karabulut , İnci M. Baytaş

Suppose $G$ is an amenable locally compact group. If $\{F_\gamma\} = \{F_\gamma\}_{\gamma\in\Gamma}$ is a F\o{}lner net for $G$, associate it with the net $\{\chi_{F_\gamma} / |F_\gamma|\} \subset L_1(G) \subset L_\infty^*(G)$. Thus, every…

Group Theory · Mathematics 2021-05-18 John Hopfensperger

Given a graph $F$, let $s_t(F)$ be the number of subdivisions of $F$, each with a different vertex set, which one can guarantee in a graph $G$ in which every edge lies in at least $t$ copies of $F$. In 1990, Tuza asked for which graphs $F$…

Combinatorics · Mathematics 2016-12-02 Hong Liu , Maryam Sharifzadeh , Katherine Staden

We design and engineer Fast-Sparse-Spanner, a simple and practical (fast and memory-efficient) algorithm for constructing sparse low stretch-factor geometric graphs on large pointsets in the plane. To our knowledge, this is the first…

Computational Geometry · Computer Science 2023-05-22 FNU Shariful , Justin Weathers , Anirban Ghosh , Giri Narasimhan

A class of random graph models is considered, combining features of exponential-family models and latent structure models, with the goal of retaining the strengths of both of them while reducing the weaknesses of each of them. An open…

Computation · Statistics 2020-07-21 Sergii Babkin , Jonathan Stewart , Xiaochen Long , Michael Schweinberger

The neighbourhood function N(t) of a graph G gives, for each t, the number of pairs of nodes <x, y> such that y is reachable from x in less that t hops. The neighbourhood function provides a wealth of information about the graph (e.g., it…

Data Structures and Algorithms · Computer Science 2011-01-27 Paolo Boldi , Marco Rosa , Sebastiano Vigna
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