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We study vertex sparsification for distances, in the setting of planar graphs with distortion: Given a planar graph $G$ (with edge weights) and a subset of $k$ terminal vertices, the goal is to construct an $\varepsilon$-emulator, which is…

Data Structures and Algorithms · Computer Science 2022-06-23 Hsien-Chih Chang , Robert Krauthgamer , Zihan Tan

We consider the classical $k$-Center problem in undirected graphs. The problem is known to have a polynomial-time 2-approximation. There are even $(2+\varepsilon)$-approximations running in near-linear time. The conventional wisdom is that…

Data Structures and Algorithms · Computer Science 2025-03-13 Ce Jin , Yael Kirkpatrick , Virginia Vassilevska Williams , Nicole Wein

We study the problem of residual error estimation for matrix and vector norms using a linear sketch. Such estimates can be used, for example, to quickly assess how useful a more expensive low-rank approximation computation will be. The…

Data Structures and Algorithms · Computer Science 2024-08-19 Yi Li , Honghao Lin , David P. Woodruff

We study the densest subgraph problem and give algorithms via multiplicative weights update and area convexity that converge in $O\left(\frac{\log m}{\epsilon^{2}}\right)$ and $O\left(\frac{\log m}{\epsilon}\right)$ iterations,…

Data Structures and Algorithms · Computer Science 2024-06-18 Ta Duy Nguyen , Alina Ene

In this paper, we consider the mixture of sparse linear regressions model. Let ${\beta}^{(1)},\ldots,{\beta}^{(L)}\in\mathbb{C}^n$ be $ L $ unknown sparse parameter vectors with a total of $ K $ non-zero coefficients. Noisy linear…

Information Theory · Computer Science 2018-08-03 Dong Yin , Ramtin Pedarsani , Yudong Chen , Kannan Ramchandran

We consider the recovery of a nonnegative vector x from measurements y = Ax, where A is an m-by-n matrix whos entries are in {0, 1}. We establish that when A corresponds to the adjacency matrix of a bipartite graph with sufficient…

Information Theory · Computer Science 2010-01-26 Venkat Chandar , Devavrat Shah , Gregory W. Wornell

We present the first linear time complexity randomized algorithms for unbiased approximation of the celebrated family of general random walk kernels (RWKs) for sparse graphs. This includes both labelled and unlabelled instances. The…

Machine Learning · Computer Science 2024-10-16 Krzysztof Choromanski , Isaac Reid , Arijit Sehanobish , Avinava Dubey

Given an undirected graph $G$ and an error parameter $\epsilon > 0$, the {\em graph sparsification} problem requires sampling edges in $G$ and giving the sampled edges appropriate weights to obtain a sparse graph $G_{\epsilon}$ with the…

Data Structures and Algorithms · Computer Science 2010-05-06 Ramesh Hariharan , Debmalya Panigrahi

We give the first O(m polylog(n)) time algorithms for approximating maximum flows in undirected graphs and constructing polylog(n) -quality cut-approximating hierarchical tree decompositions. Our algorithm invokes existing algorithms for…

Data Structures and Algorithms · Computer Science 2015-11-18 Richard Peng

We design fast deterministic algorithms for distance computation in the congested clique model. Our key contributions include: -- A $(2+\epsilon)$-approximation for all-pairs shortest paths in $O(\log^2{n} / \epsilon)$ rounds on unweighted…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-11-01 Keren Censor-Hillel , Michal Dory , Janne H. Korhonen , Dean Leitersdorf

Given a source of iid samples of edges of an input graph $G$ with $n$ vertices and $m$ edges, how many samples does one need to compute a constant factor approximation to the maximum matching size in $G$? Moreover, is it possible to obtain…

Data Structures and Algorithms · Computer Science 2019-07-15 Michael Kapralov , Slobodan Mitrović , Ashkan Norouzi-Fard , Jakab Tardos

We consider the problem of learning a graph modeling the statistical relations of the $d$ variables from a dataset with $n$ samples $X \in \mathbb{R}^{n \times d}$. Standard approaches amount to searching for a precision matrix $\Theta$…

Machine Learning · Statistics 2023-12-13 Titouan Vayer , Etienne Lasalle , Rémi Gribonval , Paulo Gonçalves

Consider the approximate sparse recovery problem: given Ax, where A is a known m-by-n dimensional matrix and x is an unknown (approximately) sparse n-dimensional vector, recover an approximation to x. The goal is to design the matrix A such…

Data Structures and Algorithms · Computer Science 2014-11-11 Arnab Bhattacharyya , Vineet Nair

We describe algorithms to efficiently compute minimum $(s,t)$-cuts and global minimum cuts of undirected surface-embedded graphs. Given an edge-weighted undirected graph $G$ with $n$ vertices embedded on an orientable surface of genus $g$,…

Data Structures and Algorithms · Computer Science 2019-10-11 Erin W. Chambers , Jeff Erickson , Kyle Fox , Amir Nayyeri

We study approximation algorithms for the following geometric version of the maximum coverage problem: Let $\mathcal{P}$ be a set of $n$ weighted points in the plane. Let $D$ represent a planar object, such as a rectangle, or a disk. We…

Computational Geometry · Computer Science 2017-12-08 Kai Jin , Jian Li , Haitao Wang , Bowei Zhang , Ningye Zhang

We develop two different methods to achieve subexponential time parameterized algorithms for problems on sparse directed graphs. We exemplify our approaches with two well studied problems. For the first problem, {\sc $k$-Leaf…

Data Structures and Algorithms · Computer Science 2010-01-07 Frederic Dorn , Fedor V. Fomin , Daniel Lokshtanov , Venkatesh Raman , Saket Saurabh

Given a weighted graph $G$ and an error parameter $\epsilon > 0$, the {\em graph sparsification} problem requires sampling edges in $G$ and giving the sampled edges appropriate weights to obtain a sparse graph $G_{\epsilon}$ (containing…

Data Structures and Algorithms · Computer Science 2010-04-26 Ramesh Hariharan , Debmalya Panigrahi

Connectivity related concepts are of fundamental interest in graph theory. The area has received extensive attention over four decades, but many problems remain unsolved, especially for directed graphs. A directed graph is 2-edge-connected…

Data Structures and Algorithms · Computer Science 2017-05-31 Shiri Chechik , Thomas Dueholm Hansen , Giuseppe F. Italiano , Veronika Loitzenbauer , Nikos Parotsidis

For a family of graphs $\cal F$, the canonical Weighted $\cal F$ Vertex Deletion problem is defined as follows: given an $n$-vertex undirected graph $G$ and a weight function $w: V(G)\rightarrow\mathbb{R}$, find a minimum weight subset…

Data Structures and Algorithms · Computer Science 2017-07-18 Akanksha Agrawal , Daniel Lokshtanov , Pranabendu Misra , Saket Saurabh , Meirav Zehavi

We study the problem of sketching an input graph, so that given the sketch, one can estimate the weight of any cut in the graph within factor $1+\epsilon$. We present lower and upper bounds on the size of a randomized sketch, focusing on…

Data Structures and Algorithms · Computer Science 2014-11-11 Alexandr Andoni , Robert Krauthgamer , David P. Woodruff
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