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Many numerical methods for evaluating matrix functions can be naturally viewed as computational graphs. Rephrasing these methods as directed acyclic graphs (DAGs) is a particularly effective approach to study existing techniques, improve…

Numerical Analysis · Mathematics 2021-08-20 Elias Jarlebring , Massimiliano Fasi , Emil Ringh

Factorization Machines (FM) are powerful class of models that incorporate higher-order interaction among features to add more expressive power to linear models. They have been used successfully in several real-world tasks such as…

Machine Learning · Computer Science 2020-04-30 Parameswaran Raman , S. V. N. Vishwanathan

Generating novel molecules with optimal properties is a crucial step in many industries such as drug discovery. Recently, deep generative models have shown a promising way of performing de-novo molecular design. Although graph generative…

Machine Learning · Computer Science 2018-11-27 Rim Assouel , Mohamed Ahmed , Marwin H Segler , Amir Saffari , Yoshua Bengio

Quantum signal processing (QSP) represents a real scalar polynomial of degree $d$ using a product of unitary matrices of size $2\times 2$, parameterized by $(d+1)$ real numbers called the phase factors. This innovative representation of…

Quantum Physics · Physics 2024-12-11 Yulong Dong , Lin Lin , Hongkang Ni , Jiasu Wang

A local algorithm is a distributed algorithm that completes after a constant number of synchronous communication rounds. We present local approximation algorithms for the minimum dominating set problem and the maximum matching problem in…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-02-02 Matti Åstrand , Valentin Polishchuk , Joel Rybicki , Jukka Suomela , Jara Uitto

We consider partitioned graphs, by which we mean finite strongly connected directed graphs with a partitioned edge set $ {\mathcal E} ={\mathcal E}^- \cup{\mathcal E}^+$. With additionally given a relation $\mathcal R$ between the edges in…

Dynamical Systems · Mathematics 2016-03-16 Wolfgang Krieger

In this paper we introduced an arithmetic graph function which associates with every group G the directed graph whose vertices corresponds to the divisors of |G|. With the help of such functions we introduced arithmetic graphs of classes of…

Group Theory · Mathematics 2015-10-14 V. I. Murashka , A. F. Vasil'ev

A claw-free graph is a graph that does not contain $K_{1,3}$ as an induced subgraph, and a 2-factor is a 2-regular spanning subgraph of a graph. In 1997, Ryj\'{a}\v{c}ek introduced the closure concept of claw-free graphs, and Hamilton…

Combinatorics · Mathematics 2025-04-14 Masaki Kashima

In [Phys. Rev. A 69, 022316 (2004)] we presented a description of the action of local Clifford operations on graph states in terms of a graph transformation rule, known in graph theory as \emph{local complementation}. It was shown that two…

Quantum Physics · Physics 2009-11-10 Maarten Van den Nest , Jeroen Dehaene , Bart De Moor

Assume that there is a free group action of automorphisms on a bipartite graph. If there is a perfect matching on the factor graph, then obviously there is a perfect matching on the graph. Surprisingly, the reversed is also true for…

Group Theory · Mathematics 2016-07-26 Jan Fricke

A \emph{locally irregular graph} is a graph whose adjacent vertices have distinct degrees. We say that a graph $G$ can be decomposed into $k$ locally irregular subgraphs if its edge set may be partitioned into $k$ subsets each of which…

Combinatorics · Mathematics 2017-03-02 Jakub Przybyło

The problem of reconstructing functions from their asymptotic expansions in powers of a small variable is addressed by deriving a novel type of approximants. The derivation is based on the self-similar approximation theory, which presents…

Statistical Mechanics · Physics 2009-11-07 S. Gluzman , V. I. Yukalov , D. Sornette

The graph Fourier transform (GFT) is an important tool for graph signal processing, with applications ranging from graph-based image processing to spectral clustering. However, unlike the discrete Fourier transform, the GFT typically does…

Signal Processing · Electrical Eng. & Systems 2019-10-02 Keng-Shih Lu , Antonio Ortega

We prove that the marginal densities of a global probability mass function in a primal normal factor graph and the corresponding marginal densities in the dual normal factor graph are related via local mappings. The mapping depends on the…

Machine Learning · Statistics 2020-07-15 Mehdi Molkaraie

While graphs and abstract data structures can be large and complex, practical instances are often regular or highly structured. If the instance has sufficient structure, we might hope to compress the object into a more succinct…

Computational Complexity · Computer Science 2024-12-02 Shreya Gupta , Boyang Huang , Russell Impagliazzo , Stanley Woo , Christopher Ye

This paper introduces and demonstrates a computational pipeline for the statistical analysis of shape graph datasets, namely geometric networks embedded in 2D or 3D spaces. Unlike traditional abstract graphs, our purpose is not only to…

Machine Learning · Computer Science 2026-02-19 Murad Hossen , Demetrio Labate , Nicolas Charon

The quadratic embedding constant (QE constant) of a graph is a new characteristic value of a graph defined through the distance matrix. We derive formulae for the QE constants of the join of two regular graphs, double graphs and certain…

Combinatorics · Mathematics 2022-09-30 Zhenzhen Lou , Nobuaki Obata , Qiongxiang Huang

Graph partitioning is a key fundamental problem in the area of big graph computation. Previous works do not consider the practical requirements when optimizing the big data analysis in real applications. In this paper, motivated by…

Databases · Computer Science 2024-04-10 Baoling Ning , Jianzhong Li

Girth-regular graphs with equal girth, regular degree and chromatic index are studied for the determination of 1-factorizations with each 1-factor intersecting every girth cycle. Applications to hamiltonian decomposability and to…

Combinatorics · Mathematics 2025-10-15 Italo J. Dejter

Factorization machine (FM) is a prevalent approach to modeling pairwise (second-order) feature interactions when dealing with high-dimensional sparse data. However, on the one hand, FM fails to capture higher-order feature interactions…

Machine Learning · Computer Science 2025-02-24 Shu Wu , Zekun Li , Yunyue Su , Zeyu Cui , Xiaoyu Zhang , Liang Wang