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This article proposes a novel methodology to learn a stable robot control law driven by dynamical systems. The methodology requires a single demonstration and can deduce a stable dynamics in arbitrary high dimensions. The method relies on…

Robotics · Computer Science 2022-07-19 Sthithpragya Gupta , Aradhana Nayak , Aude Billard

The standard notion of the Laplacian of a graph is generalized to the setting of a graph with the extra structure of a ``transmission`` system. A transmission system is a mathematical representation of a means of transmitting…

Combinatorics · Mathematics 2009-12-22 Sylvain E. Cappell , Edward Y. Miller

In this paper, we propose a modularized framework for communication processes applicable to crash and Byzantine fault-tolerant consensus protocols. We abstract basic communication components and show that the communication process of the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-18 Yuetai Li , Zhangchen Xu , Yiqi Wang , Zihan Zhou , Lei Zhang , Jon Crowcroft

We study distributed optimization of finite-degree polynomial Laplacian spectral objectives under fixed topology and a global weight budget, targeting the collective behavior of the entire spectrum rather than a few extremal eigenvalues. By…

Optimization and Control · Mathematics 2025-12-16 Jitian Liu , Nicolas Kozachuk , Subhrajit Bhattacharya

This paper addresses the robust consensus problem under switching topologies. Contrary to existing methods, the proposed approach provides decentralized protocols that achieve consensus for networked multi-agent systems in a predefined…

Optimization and Control · Mathematics 2019-08-02 R. Aldana-López , D. Gómez-Gutiérrez , M. Defoort , J. D. Sánchez-Torres , A. J. Muñoz-Vázquez

The normalized distance Laplacian of a graph $G$ is defined as $\mathcal{D}^\mathcal{L}(G)=T(G)^{-1/2}(T(G)-\mathcal{D}(G))T(G)^{-1/2}$ where $\mathcal{D}(G)$ is the matrix with pairwise distances between vertices and $T(G)$ is the diagonal…

Combinatorics · Mathematics 2023-02-23 Jacob Johnston , Michael Tait

We propose a generalized debiased Lasso estimator based on a stability principle. When a single column of the design matrix is perturbed, the estimator admits a simple update formula that can be computed from the original solution. Under…

Statistics Theory · Mathematics 2026-04-14 Jingbo Liu

In this article, we study random graphs with a given degree sequence $d_1, d_2, \cdots, d_n$ from the configuration model. We show that under mild assumptions of the degree sequence, the spectral distribution of the normalized Laplacian…

Probability · Mathematics 2024-12-04 Shuyi Wang , Kevin Li , Jiaoyang Huang

This paper addresses the distributed consensus design problem for linear multi-agent systems with directed communication graphs and external disturbances. Both the cases with strongly connected communication graphs and leader-follower…

Systems and Control · Computer Science 2015-02-03 Zhongkui Li , Zhisheng Duan

Contemporary technological challenges often involve many degrees of freedom in a distributed or networked setting. Three aspects are notable: the variables are usually associated with the nodes of a graph with limited communication…

Statistical Mechanics · Physics 2017-08-30 Nicolas Allegra , Bassam Bamieh , Partha P. Mitra , Clément Sire

Simplicial complexes are generalizations of graphs that describe higher-order network interactions among nodes in the graph. Network dynamics described by graph Laplacian flows have been widely studied in network science and control theory,…

Optimization and Control · Mathematics 2026-02-04 Mathias Hudoba de Badyn , Tyler Summers

Manifold learning methods play a prominent role in nonlinear dimensionality reduction and other tasks involving high-dimensional data sets with low intrinsic dimensionality. Many of these methods are graph-based: they associate a vertex…

Machine Learning · Computer Science 2021-11-16 Joe Kileel , Amit Moscovich , Nathan Zelesko , Amit Singer

The common graph Laplacian regularizer is well-established in semi-supervised learning and spectral dimensionality reduction. However, as a first-order regularizer, it can lead to degenerate functions in high-dimensional manifolds. The…

Computer Vision and Pattern Recognition · Computer Science 2016-02-12 Kwang In Kim , James Tompkin , Hanspeter Pfister , Christian Theobalt

We consider the problem of finding universal bounds of "isoperimetric" or "isodiametric" type on the spectral gap of the Laplacian on a metric graph with natural boundary conditions at the vertices, in terms of various analytical and…

Spectral Theory · Mathematics 2016-08-24 James B. Kennedy , Pavel Kurasov , Gabriela Malenova , Delio Mugnolo

The basic inverse problem in spectral graph theory consists in determining the graph given its eigenvalue spectrum. In this paper, we are interested in a network of technological agents whose graph is unknown, communicating by means of a…

Mathematical Physics · Physics 2013-08-20 Enzo Fioriti , Stefano Chiesa , Fabio Fratichini

A network of coupled dynamical systems is represented by a graph whose vertices represent individual cells and whose edges represent couplings between cells. Motivated by the impact of synchronization results of the Kuramoto networks, we…

Dynamical Systems · Mathematics 2023-10-10 Tiago Amorim , Miriam Manoel

We propose the notion of normalized Laplacian matrix $\mathcal{L}(\Phi)$ for a gain graphs and study its properties in detail, providing insights and counterexamples along the way. We establish bounds for the eigenvalues of…

Combinatorics · Mathematics 2022-03-11 M. Rajesh Kannan , Navish Kumar , Shivaramakrishna Pragada

We use a conformal mapping technique to study the Laplacian transfer across a rough interface. Natural Dirichlet or Von Neumann boundary condition are simply read by the conformal map. Mixed boundary condition, albeit being more complex can…

Other Condensed Matter · Physics 2016-08-16 Damien Vandembroucq , Stéphane Roux

Recently normalized Laplacian matrices of graphs are studied as density matrices in quantum mechanics. Separability and entanglement of density matrices are important properties as they determine the nonclassical behavior in quantum…

Quantum Physics · Physics 2017-02-28 Chai Wah Wu

Symmetric matrices with zero row sums occur in many theoretical settings and in real-life applications. When the offdiagonal elements of such matrices are i.i.d. random variables and the matrices are large, the eigenvalue distributions…

Disordered Systems and Neural Networks · Physics 2023-06-27 Pawat Akara-pipattana , Oleg Evnin
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