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For a connected weighted hypergraph, we give a randomized almost-linear-time solver for the Poisson problem for the cut-based hypergraph Laplacian in the natural input size $P=\sum_{e\in E}|e|$, the sum of hyperedge sizes. For every fixed…

Data Structures and Algorithms · Computer Science 2026-05-01 Yuichi Yoshida

We give an approximation algorithm for Quantum Max-Cut which works by rounding an SDP relaxation to an entangled quantum state. The SDP is used to choose the parameters of a variational quantum circuit. The entangled state is then…

Quantum Physics · Physics 2023-11-15 Robbie King

Finding a maximum cut is a fundamental task in many computational settings. Surprisingly, it has been insufficiently studied in the classic distributed settings, where vertices communicate by synchronously sending messages to their…

Data Structures and Algorithms · Computer Science 2017-07-27 Keren Censor-Hillel , Rina Levy , Hadas Shachnai

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

We prove that the maximum eigenvalue of the (both signed and unsigned) Laplacian of level $k$ Kikuchi graph of any graph $G$ with $m$ edges is at most $m+k$. This confirms four recent conjectures of Apte, Parekh, and Sud. As applications,…

Quantum Physics · Physics 2026-05-15 Ainesh Bakshi , Arpon Basu , Pravesh Kothari , Anqi Li

Whether or not the Sparsest Cut problem admits an efficient $O(1)$-approximation algorithm is a fundamental algorithmic question with connections to geometry and the Unique Games Conjecture. Revisiting spectral algorithms for Sparsest Cut,…

Data Structures and Algorithms · Computer Science 2025-10-01 Tommaso d'Orsi , Chris Jones , Jake Ruotolo , Salil Vadhan , Jiyu Zhang

We investigate the convergence properties of exact and inexact forward-backward algorithms to minimise the sum of two weakly convex functions defined on a Hilbert space, where one has a Lipschitz-continuous gradient. We show that the exact…

Optimization and Control · Mathematics 2024-06-24 Ewa Bednarczuk , Giovanni Bruccola , Gabriele Scrivanti , The Hung Tran

We design new approximation algorithms for the Multiway Cut problem, improving the previously known factor of 1.32388 [Buchbinder et al., 2013]. We proceed in three steps. First, we analyze the rounding scheme of Buchbinder et al., 2013 and…

Data Structures and Algorithms · Computer Science 2014-05-13 Ankit Sharma , Jan Vondrák

We provide new insight into the convergence properties of the Douglas-Rachford algorithm for the problem $\min_x \{f(x)+g(x)\}$, where $f$ and $g$ are convex functions. Our approach relies on and highlights the natural primal-dual symmetry…

Optimization and Control · Mathematics 2021-11-12 Javier Peña , Juan C. Vera , Luis F. Zuluaga

We consider a primal-dual algorithm for minimizing $f(x)+h\square l(Ax)$ with Fr\'echet differentiable $f$ and $l^*$. This primal-dual algorithm has two names in literature: Primal-Dual Fixed-Point algorithm based on the Proximity Operator…

Optimization and Control · Mathematics 2021-02-02 Zhi Li , Ming Yan

$k$-Coloring Reconfiguration is one of the most well-studied reconfiguration problems, which asks to transform a given proper $k$-coloring of a graph to another by repeatedly recoloring a single vertex. Its approximate version, Maxmin…

Computational Complexity · Computer Science 2025-04-01 Shuichi Hirahara , Naoto Ohsaka

This paper presents a modified iterative approach to solve the variational inequality problem using the double inertial technique in the context of a real Hilbert space. Our iterative technique involves a projection onto a generalized…

Functional Analysis · Mathematics 2026-03-19 Watanjeet Singh , Sumit Chandok

We construct a least squares approximation method for the recovery of complex-valued functions from a reproducing kernel Hilbert space on $D \subset \mathbb{R}^d$. The nodes are drawn at random for the whole class of functions and the error…

Numerical Analysis · Mathematics 2021-04-05 Lutz Kämmerer , Tino Ullrich , Toni Volkmer

We study alternating first-order algorithms with no inner loops for solving nonconvex-strongly-concave min-max problems. We show the convergence of the alternating gradient descent--ascent algorithm method by proposing a substantially…

Optimization and Control · Mathematics 2026-03-31 Guido Tapia-Riera , Camille Castera , Nicolas Papadakis

The authors in (Banjac et al., 2019) recently showed that the Douglas-Rachford algorithm provides certificates of infeasibility for a class of convex optimization problems. In particular, they showed that the difference between consecutive…

Optimization and Control · Mathematics 2021-02-08 Goran Banjac , John Lygeros

The objective of this paper is to develop methods for solving image recovery problems subject to constraints on the solution. More precisely, we will be interested in problems which can be formulated as the minimization over a closed convex…

Optimization and Control · Mathematics 2012-12-12 Caroline Chaux , Jean-Christophe Pesquet , Nelly Pustelnik

We prove two generalizations of the Cheeger's inequality. The first generalization relates the second eigenvalue to the edge expansion and the vertex expansion of the graph G, $\lambda_2 = \Omega(\phi^V(G) \phi(G))$, where $\phi^V(G)$…

Data Structures and Algorithms · Computer Science 2015-04-06 Tsz Chiu Kwok , Lap Chi Lau , Yin Tat Lee

We propose to generate Lagrangian cut for two-stage stochastic integer program by batch, in contrast to the existing methods which solve each Lagrangian subproblem at every iteration. We establish two convergence properties of the proposed…

Optimization and Control · Mathematics 2024-01-30 Luo Xiaoyu , Gao Chuanhou

We introduce a set of multi-way dual Cheeger constants and prove universal higher-order dual Cheeger inequalities for eigenvalues of normalized Laplace operators on weighted finite graphs. Our proof proposes a new spectral clustering…

Spectral Theory · Mathematics 2014-10-14 Shiping Liu

We investigate the continuous non-monotone DR-submodular maximization problem subject to a down-closed convex solvable constraint. Our first contribution is to construct an example to demonstrate that (first-order) stationary points can…

Data Structures and Algorithms · Computer Science 2024-03-27 Shengminjie Chen , Donglei Du , Wenguo Yang , Dachuan Xu , Suixiang Gao