English
Related papers

Related papers: The $1$-Laplacian Cheeger Cut: Theory and Algorith…

200 papers

We present a generic framework for parallel coordinate descent (CD) algorithms that includes, as special cases, the original sequential algorithms Cyclic CD and Stochastic CD, as well as the recent parallel Shotgun algorithm. We introduce…

Machine Learning · Computer Science 2012-07-04 Chad Scherrer , Mahantesh Halappanavar , Ambuj Tewari , David Haglin

We consider the problem of identifying a maximum clique in a given graph. We have proposed a mathematical model for this problem. The model resembles the matrix decomposition of the adjacency matrix of a given graph. The objective function…

Optimization and Control · Mathematics 2023-07-19 Salma Omer , Montaz Ali

We present a prescription to calculate the quadratic and logarithmic divergent parts of several integrals employing a cutoff in a coherent way, i.e. in total agreement with symmetry requirements. As examples we consider one-loop Ward…

High Energy Physics - Phenomenology · Physics 2008-11-26 T. Varin , D. Davesne , M. Oertel , M. Urban

This paper shows that dimensionality reduction methods such as UMAP and t-SNE, can be approximately recast as MAP inference methods corresponding to a model introduced in Ravuri et al. (2023), that describes the graph Laplacian (an estimate…

Machine Learning · Statistics 2025-05-13 Aditya Ravuri , Neil D. Lawrence

To numerically solve a generic elliptic equation on two-dimensional domains with rectangular Cartesian grids, we propose a cut-cell geometric multigrid method that features (1) general algorithmic steps that apply to two-dimensional…

Numerical Analysis · Mathematics 2026-01-19 Jiyu Liu , Zhixuan Li , Jiatu Yan , Zhiqi Li , Qinghai Zhang

Graph sparsification underlies a large number of algorithms, ranging from approximation algorithms for cut problems to solvers for linear systems in the graph Laplacian. In its strongest form, "spectral sparsification" reduces the number of…

Quantum Physics · Physics 2023-05-09 Simon Apers , Ronald de Wolf

Canonical Polyadic Decomposition (CPD) of a third-order tensor is a minimal decomposition into a sum of rank-$1$ tensors. We find new mild deterministic conditions for the uniqueness of individual rank-$1$ tensors in CPD and present an…

Spectral Theory · Mathematics 2016-07-20 Ignat Domanov , Lieven De Lathauwer

In a recent paper, Bubeck, Lee, and Singh introduced a new first order method for minimizing smooth strongly convex functions. Their geometric descent algorithm, largely inspired by the ellipsoid method, enjoys the optimal linear rate of…

Optimization and Control · Mathematics 2017-03-02 Dmitriy Drusvyatskiy , Maryam Fazel , Scott Roy

A cell-centered implicit-explicit updated Lagrangian finite volume scheme on unstructured grids is proposed for a unified first order hyperbolic formulation of continuum fluid and solid mechanics. The scheme provably respects the stiff…

Numerical Analysis · Mathematics 2022-01-26 Walter Boscheri , Simone Chiocchetti , Ilya Peshkov

A new algorithm for solving large-scale convex optimization problems with a separable objective function is proposed. The basic idea is to combine three techniques: Lagrangian dual decomposition, excessive gap and smoothing. The main…

Optimization and Control · Mathematics 2011-12-01 Tran Dinh Quoc , Carlo Savorgnan , Moritz Diehl

One of the major challenges in the Bayesian solution of inverse problems governed by partial differential equations (PDEs) is the computational cost of repeatedly evaluating numerical PDE models, as required by Markov chain Monte Carlo…

Computation · Statistics 2016-05-03 Tiangang Cui , Youssef M. Marzouk , Karen E. Willcox

C-dismantling (CD) problem aims at finding the minimum vertex set D of a graph G(V,E) after removing which the remaining graph will break into connected components with the size not larger than C. In this paper, we introduce a spin-glass…

Physics and Society · Physics 2018-12-26 Shao-Meng Qin

The celebrated Cheeger's Inequality \cite{am85,a86} establishes a bound on the expansion of a graph via its spectrum. This inequality is central to a rich spectral theory of graphs, based on studying the eigenvalues and eigenvectors of the…

Discrete Mathematics · Computer Science 2014-10-31 Anand Louis

Structural parameters of graph (such as degeneracy and arboricity) had rarely been considered when designing algorithms for $\textit{(edge) clique cover}$ problems. Taking degeneracy of graph into account, we present a greedy framework and…

Data Structures and Algorithms · Computer Science 2022-09-07 Ahammed Ullah

We introduce a variant of (sparse) PCA in which the set of feasible support sets is determined by a graph. In particular, we consider the following setting: given a directed acyclic graph $G$ on $p$ vertices corresponding to variables, the…

Structured prediction can be thought of as a simultaneous prediction of multiple labels. This is often done by maximizing a score function on the space of labels, which decomposes as a sum of pairwise and unary potentials. The above is…

Machine Learning · Computer Science 2021-02-19 Kevin Bello , Jean Honorio

In this paper, we study reversibility of one-dimensional(1D) linear cellular automata(LCA) under null boundary condition, whose core problems have been divided into two main parts: calculating the period of reversibility and verifying the…

Computational Complexity · Computer Science 2019-07-16 Xinyu Du , Chao Wang , Tianze Wang , Zeyu Gao

We introduce a family of reductions for removing proper and homogeneous pairs of cliques from a graph G. This family generalizes some routines presented in the literature, mostly in the context of claw-free graphs. These reductions can be…

Optimization and Control · Mathematics 2011-03-15 Yuri Faenza , Gianpaolo Oriolo , Claudia Snels

Expander decompositions of graphs have significantly advanced the understanding of many classical graph problems and led to numerous fundamental theoretical results. However, their adoption in practice has been hindered due to their…

Data Structures and Algorithms · Computer Science 2026-04-27 Kathrin Hanauer , Monika Henzinger , Robin Münk , Harald Räcke , Maximilian Vötsch

Many codes have been developed to study highly relativistic, magnetized flows around and inside compact objects. Depending on the adopted formalism, some of these codes evolve the vector potential $\mathbf{A}$, and others evolve the…

Computational Physics · Physics 2019-01-30 Zachary J. Silberman , Thomas R. Adams , Joshua A. Faber , Zachariah B. Etienne , Ian Ruchlin