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In this paper, we introduce a graph matching method that can account for constraints of arbitrary order, with arbitrary potential functions. Unlike previous decomposition approaches that rely on the graph structures, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2018-02-26 D. Khuê Lê-Huu , Nikos Paragios

We present new min-max relations in digraphs between the number of paths satisfying certain conditions and the order of the corresponding cuts. We define these objects in order to capture, in the context of solving the half-integral linkage…

Combinatorics · Mathematics 2023-06-29 Victor Campos , Jonas Costa , Raul Lopes , Ignasi Sau

We investigate the three-dimensional compressible Euler-Maxwell system, a model for simulating the transport of electrons interacting with propagating electromagnetic waves in semiconductor devices. First, we show the global well-posedness…

Analysis of PDEs · Mathematics 2024-07-02 Timothée Crin-Barat , Yue-Jun Peng , Ling-Yun Shou , Jiang Xu

Many combinatorial optimization problems can be phrased in the language of constraint satisfaction problems. We introduce a graph neural network architecture for solving such optimization problems. The architecture is generic; it works for…

Artificial Intelligence · Computer Science 2020-02-12 Jan Toenshoff , Martin Ritzert , Hinrikus Wolf , Martin Grohe

We present a randomized augmenting paths-based algorithm to compute the maximum flow in a directed, uncapacitated graph in almost $m+nF$ time, matching the algorithm of Karger and Levine for undirected graphs (SICOMP 2015). Combined with an…

Data Structures and Algorithms · Computer Science 2026-04-17 Jason Li

TheL2-gain characterizes a dynamical system's input-output properties, but can be difficult to determine for nonlinear systems. Previous work designed a nonconvex optimization problem to simultaneously search for a continuous piecewise…

Optimization and Control · Mathematics 2024-10-18 Amy Strong , Reza Lavaei , Leila J. Bridgeman

We propose an autoregressive framework for modelling dynamic networks with dependent edges. It encompasses models that accommodate, for example, transitivity, degree heterogenenity, and other stylized features often observed in real network…

Statistics Theory · Mathematics 2026-03-25 Jinyuan Chang , Qin Fang , Eric D. Kolaczyk , Peter W. MacDonald , Qiwei Yao

Alternatives to recurrent neural networks, in particular, architectures based on attention or convolutions, have been gaining momentum for processing input sequences. In spite of their relevance, the computational properties of these…

Machine Learning · Computer Science 2019-01-14 Jorge Pérez , Javier Marinković , Pablo Barceló

We formulate and solve a class of finite-time transport and mixing problems in the set-oriented framework. The aim is to obtain optimal discrete-time perturbations in nonlinear dynamical systems to transport a specified initial measure on…

Dynamical Systems · Mathematics 2017-11-22 Piyush Grover , Karthik Elamvazhuthi

Recent advances in dynamic graph processing have enabled the analysis of highly dynamic graphs with change at rates as high as millions of edge changes per second. Solutions in this domain, however, have been demonstrated only for…

Data Structures and Algorithms · Computer Science 2023-11-14 Juntong Luo , Scott Sallinen , Matei Ripeanu

We study the implicit bias of gradient flow (i.e., gradient descent with infinitesimal step size) on linear neural network training. We propose a tensor formulation of neural networks that includes fully-connected, diagonal, and…

Machine Learning · Computer Science 2021-09-13 Chulhee Yun , Shankar Krishnan , Hossein Mobahi

Beyond-planarity focuses on the study of geometric and topological graphs that are in some sense nearly-planar. Here, planarity is relaxed by allowing edge crossings, but only with respect to some local forbidden crossing configurations.…

Discrete Mathematics · Computer Science 2017-12-29 Patrizio Angelini , Michael A. Bekos , Michael Kaufmann , Maximilian Pfister , Torsten Ueckerdt

There is a deep and interesting connection between the topological properties of a graph and the behaviour of the dynamical system defined on it. We analyse various kind of graphs, with different contrasting connectivity or degree…

Combinatorics · Mathematics 2017-05-01 Barbara Giunti , Vincenzo Perri

This note is concerned with the linear matrix equation $X = AX^\top B + C$, where the operator $(\cdot)^\top$ denotes the transpose ($\top$) of a matrix. The first part of this paper set forth the necessary and sufficient conditions for the…

Numerical Analysis · Mathematics 2014-02-10 Chun-Yueh Chiang

We introduce and investigate the approximability of the maximum binary tree problem (MBT) in directed and undirected graphs. The goal in MBT is to find a maximum-sized binary tree in a given graph. MBT is a natural variant of the…

Discrete Mathematics · Computer Science 2020-07-24 Karthekeyan Chandrasekaran , Elena Grigorescu , Gabriel Istrate , Shubhang Kulkarni , Young-San Lin , Minshen Zhu

We introduce the notion of balance for directed graphs: a weighted directed graph is $\alpha$-balanced if for every cut $S \subseteq V$, the total weight of edges going from $S$ to $V\setminus S$ is within factor $\alpha$ of the total…

Data Structures and Algorithms · Computer Science 2016-03-31 Alina Ene , Gary Miller , Jakub Pachocki , Aaron Sidford

A direct transient growth analysis for three-dimensional perturbations to flow past a periodic array of T-106/300 low-pressure turbine fan blades is presented. The methodology is based on a singular value decomposition of the flow evolution…

Fluid Dynamics · Physics 2013-02-13 AS Sharma , N Abdessemed , SJ Sherwin , V Theofilis

The statistical leverage scores of a complex matrix $A\in\mathbb{C}^{n\times d}$ record the degree of alignment between col$(A)$ and the coordinate axes in $\mathbb{C}^n$. These score are used in random sampling algorithms for solving…

Machine Learning · Statistics 2016-10-03 James Hook

We study cross-graph charging schemes for graphs drawn in the plane. These are charging schemes where charge is moved across vertices of different graphs. Such methods have been recently applied to obtain various properties of…

Computational Geometry · Computer Science 2012-09-04 Micha Sharir , Adam Sheffer

Traditional algorithms to optimize artificial neural networks when confronted with a supervised learning task are usually exploitation-type relaxational dynamics such as gradient descent (GD). Here, we explore the dynamics of the neural…

Machine Learning · Computer Science 2026-03-10 Pedro Jiménez-González , Miguel C. Soriano , Lucas Lacasa