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We develop a new framework for generalizing approximation algorithms from the structural graph algorithm literature so that they apply to graphs somewhat close to that class (a scenario we expect is common when working with real-world…

In this paper, we propose and study a new semi-random model for graph partitioning problems. We believe that it captures many properties of real--world instances. The model is more flexible than the semi-random model of Feige and Kilian and…

Data Structures and Algorithms · Computer Science 2015-03-20 Konstantin Makarychev , Yury Makarychev , Aravindan Vijayaraghavan

We design approximation algorithms for Unique Games when the constraint graph admits good low diameter graph decomposition. For the ${\sf Max2Lin}_k$ problem in $K_r$-minor free graphs, when there is an assignment satisfying $1-\varepsilon$…

Data Structures and Algorithms · Computer Science 2017-12-01 Vedat Levi Alev , Lap Chi Lau

We consider the semi-random graph model of [Makarychev, Makarychev and Vijayaraghavan, STOC'12], where, given a random bipartite graph with $\alpha$ edges and an unknown bipartition $(A, B)$ of the vertex set, an adversary can add arbitrary…

Data Structures and Algorithms · Computer Science 2024-06-10 Vincent Cohen-Addad , Tommaso d'Orsi , Aida Mousavifar

We provide a randomized linear time approximation scheme for a generic problem about clustering of binary vectors subject to additional constrains. The new constrained clustering problem encompasses a number of problems and by solving it,…

Data Structures and Algorithms · Computer Science 2018-07-20 Fedor V. Fomin , Petr A. Golovach , Daniel Lokshtanov , Fahad Panolan , Saket Saurabh

The Sparsest Cut is a fundamental optimization problem that has been extensively studied. For planar inputs the problem is in $P$ and can be solved in $\tilde{O}(n^3)$ time if all vertex weights are $1$. Despite a significant amount of…

Data Structures and Algorithms · Computer Science 2020-07-07 Amir Abboud , Vincent Cohen-Addad , Philip N. Klein

We study matrix sketching methods for regularized variants of linear regression, low rank approximation, and canonical correlation analysis. Our main focus is on sketching techniques which preserve the objective function value for…

Data Structures and Algorithms · Computer Science 2017-06-27 Haim Avron , Kenneth L. Clarkson , David P. Woodruff

Distributed network optimization algorithms, such as minimum spanning tree, minimum cut, and shortest path, are an active research area in distributed computing. This paper presents a fast distributed algorithm for such problems in the…

Data Structures and Algorithms · Computer Science 2018-05-29 Bernhard Haeupler , Jason Li , Goran Zuzic

We introduce a new variant of Szemer\'edi's regularity lemma which we call the "sparse regular approximation lemma" (SRAL). The input to this lemma is a graph $G$ of edge density $p$ and parameters $\epsilon, \delta$, where we think of…

Combinatorics · Mathematics 2016-10-11 Guy Moshkovitz , Asaf Shapira

Recently, Brandt et al. [STOC'16] proved a lower bound for the distributed Lov\'asz Local Lemma, which has been conjectured to be tight for sufficiently relaxed LLL criteria by Chang and Pettie [FOCS'17]. At the heart of their result lies a…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-27 Sebastian Brandt

We develop a family of accelerated stochastic algorithms that minimize sums of convex functions. Our algorithms improve upon the fastest running time for empirical risk minimization (ERM), and in particular linear least-squares regression,…

Machine Learning · Statistics 2015-06-25 Roy Frostig , Rong Ge , Sham M. Kakade , Aaron Sidford

Inspired by previous work of Diaz, Petit, Serna, and Trevisan (Approximating layout problems on random graphs Discrete Mathematics, 235, 2001, 245--253), we show that several well-known graph layout problems are approximable to within a…

Combinatorics · Mathematics 2017-10-31 Kevin K. H. Cheung , Patrick D. Girardet

While Szemer\'edi's graph regularity lemma is an indispensable tool for studying extremal problems in graph theory, using it comes with a hefty price, since a worst-case graph may only have regular partitions of tower-type size. It is thus…

Combinatorics · Mathematics 2025-08-14 Lior Gishboliner , Asaf Shapira , Yuval Wigderson

Introduced in the mid-1970's as an intermediate step in proving a long-standing conjecture on arithmetic progressions, Szemer\'edi's regularity lemma has emerged over time as a fundamental tool in different branches of graph theory,…

Computer Vision and Pattern Recognition · Computer Science 2016-09-22 Marcello Pelillo , Ismail Elezi , Marco Fiorucci

In this paper we give fast distributed graph algorithms for detecting and listing small subgraphs, and for computing or approximating the girth. Our algorithms improve upon the state of the art by polynomial factors, and for girth, we…

Data Structures and Algorithms · Computer Science 2021-01-20 Keren Censor-Hillel , Orr Fischer , Tzlil Gonen , François Le Gall , Dean Leitersdorf , Rotem Oshman

We study the classical scheduling problem on parallel machines %with precedence constraints where the precedence graph has the bounded depth $h$. Our goal is to minimize the maximum completion time. We focus on developing approximation…

Data Structures and Algorithms · Computer Science 2023-02-02 Bin Fu , Yumei Huo , Hairong Zhao

We prove a lower bound on the space complexity of two-pass semi-streaming algorithms that approximate the maximum matching problem. The lower bound is parameterized by the density of Ruzsa-Szemeredi graphs: * Any two-pass semi-streaming…

Data Structures and Algorithms · Computer Science 2021-08-17 Sepehr Assadi

We design an algorithm for approximating the size of \emph{Max Cut} in dense graphs. Given a proximity parameter $\varepsilon \in (0,1)$, our algorithm approximates the size of \emph{Max Cut} of a graph $G$ with $n$ vertices, within an…

Data Structures and Algorithms · Computer Science 2021-12-21 Arijit Ghosh , Gopinath Mishra , Rahul Raychaudhury , Sayantan Sen

Vertex connectivity is a well-studied concept in graph theory with numerous applications. A graph is $k$-connected if it remains connected after removing any $k-1$ vertices. The vertex connectivity of a graph is the maximum $k$ such that…

Data Structures and Algorithms · Computer Science 2021-03-30 Max Franck , Sorrachai Yingchareonthawornchai

The input to the Multiway Cut problem is a weighted undirected graph, with nonnegative edge weights, and $k$ designated terminals. The goal is to partition the vertices of the graph into $k$ parts, each containing exactly one of the…

Data Structures and Algorithms · Computer Science 2026-03-31 Joshua Brakensiek , Neng Huang , Aaron Potechin , Uri Zwick