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A central challenge in property testing is verifying algebraic structure with minimal access to data. A landmark result addressing this challenge, the linearity test of Blum, Luby, and Rubinfeld (JCSS `93), spurred a rich body of work on…

Data Structures and Algorithms · Computer Science 2025-12-01 Esty Kelman , Uri Meir , Debanuj Nayak , Sofya Raskhodnikova

A distance estimator for a graph property $\mathcal{P}$ is an algorithm that given $G$ and $\alpha, \varepsilon >0$ distinguishes between the case that $G$ is $(\alpha-\varepsilon)$-close to $\mathcal{P}$ and the case that $G$ is…

Combinatorics · Mathematics 2023-05-10 Lior Gishboliner , Nick Kushnir , Asaf Shapira

An ordered graph is a graph with a total order over its vertices. A linear layout of an ordered graph is a partition of the edges into sets of either non-crossing edges, called stacks, or non-nesting edges, called queues. The stack (queue)…

Discrete Mathematics · Computer Science 2024-12-18 Deborah Haun , Laura Merker , Sergey Pupyrev

After a somewhat rocky start, geometry and topology have established a foothold in machine learning. Message passing, either on graphs or higher-order complexes, is one of the main drivers of geometric deep learning, and paradigms that were…

Machine Learning · Computer Science 2026-05-11 Bastian Rieck

Optimal transport (OT) distances between probability distributions are parameterized by the ground metric they use between observations. Their relevance for real-life applications strongly hinges on whether that ground metric parameter is…

Machine Learning · Statistics 2020-11-06 Matthieu Heitz , Nicolas Bonneel , David Coeurjolly , Marco Cuturi , Gabriel Peyré

We continue and extend previous work on the parameterized complexity analysis of the NP-hard Stable Roommates with Ties and Incomplete Lists problem, thereby strengthening earlier results both on the side of parameterized hardness as well…

Computational Complexity · Computer Science 2021-03-09 Robert Bredereck , Klaus Heeger , Dušan Knop , Rolf Niedermeier

Graph neural networks (GNNs) have emerged as a versatile and efficient option for modeling the dynamic behavior of deformable materials. While GNNs generalize readily to arbitrary shapes, mesh topologies, and material parameters, existing…

Machine Learning · Computer Science 2026-04-30 Jiahong Wang , Logan Numerow , Stelian Coros , Christian Theobalt , Vahid Babaei , Bernhard Thomaszewski

We investigate certain structural properties of random interdependent networks. We start by studying a property known as $r$-robustness, which is a strong indicator of the ability of a network to tolerate structural perturbations and…

Social and Information Networks · Computer Science 2015-08-18 Ebrahim Moradi Shahrivar , Mohammad Pirani , Shreyas Sundaram

Large real-life complex networks are often modeled by various random graph constructions and hundreds of further references therein. In many cases it is not at all clear how the modeling strength of differently generated random graph model…

Data Structures and Algorithms · Computer Science 2020-09-01 András Faragó , Rupei Xu

One of the most fundamental questions in graph property testing is to characterize the combinatorial structure of properties that are testable with a constant number of queries. We work towards an answer to this question for the…

Data Structures and Algorithms · Computer Science 2018-11-08 Hendrik Fichtenberger , Pan Peng , Christian Sohler

We present new families of goodness-of-fit tests of uniformity on a full-dimensional set $W\subset\R^d$ based on statistics related to edge lengths of random geometric graphs. Asymptotic normality of these statistics is proven under the…

Statistics Theory · Mathematics 2020-07-20 Bruno Ebner , Franz Nestmann , Matthias Schulte

For a property $P$ and a sub-property $P'$, we say that $P$ is $P'$-partially testable with $q$ queries if there exists an algorithm that distinguishes, with high probability, inputs in $P'$ from inputs $\epsilon$-far from $P$ by using $q$…

Computational Complexity · Computer Science 2013-06-07 Eldar Fischer , Yonatan Goldhirsh , Oded Lachish

Due to the lack of long-range order, it remains challenging to characterize the structure of disordered solids and understand the nature of the glass transition. Here we propose a new structural order parameter by taking into account…

Soft Condensed Matter · Physics 2024-08-26 Ding Xu , Qinyi Liao , Ning Xu

In this paper, we study the problem of constructing a network by observing ordered connectivity constraints, which we define herein. These ordered constraints are made to capture realistic properties of real-world problems that are not…

Data Structures and Algorithms · Computer Science 2017-02-24 Yi Huang , Mano Vikash Janardhanan , Lev Reyzin

P-time event graphs are discrete event systems able to model cyclic production systems where tasks need to be performed within given time windows. Consistency is the property of admitting an infinite execution of such tasks that does not…

Logic in Computer Science · Computer Science 2026-02-10 Davide Zorzenon , Jörg Raisch

We propose the notion of {\it resistance of a graph} as an accompanying notion of the structure entropy to measure the force of the graph to resist cascading failure of strategic virus attacks. We show that for any connected network $G$,…

Discrete Mathematics · Computer Science 2018-01-11 Angsheng Li , Yicheng Pan

We show that the only random orderings of finite graphs that are invariant under isomorphism and induced subgraph are the uniform random orderings. We show how this implies the unique ergodicity of the automorphism group of the random…

Dynamical Systems · Mathematics 2018-09-10 Omer Angel , Alexander S. Kechris , Russell Lyons

Hamiltonian cycles in graphs were first studied in the 1850s. Since then, an impressive amount of research has been dedicated to identifying classes of graphs that allow Hamiltonian cycles, and to related questions. The corresponding…

Discrete Mathematics · Computer Science 2023-06-22 Isolde Adler , Noleen Köhler

Evaluating conjunctive queries and solving constraint satisfaction problems are fundamental problems in database theory and artificial intelligence, respectively. These problems are NP-hard, so that several research efforts have been made…

Databases · Computer Science 2013-01-01 Gianluigi Greco , Francesco Scarcello

Transformer-based object detectors (DETR) have shown significant performance across machine vision tasks, ultimately in object detection. This detector is based on a self-attention mechanism along with the transformer encoder-decoder…

Computer Vision and Pattern Recognition · Computer Science 2023-10-16 Zhao Ning Zou , Yuhang Zhang , Robert Wijaya
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