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We study the problem of computing a minimum cut in a simple, undirected graph and give a deterministic $O(m \log^2 n \log\log^2 n)$ time algorithm. This improves both on the best previously known deterministic running time of $O(m \log^{12}…

Data Structures and Algorithms · Computer Science 2019-11-11 Monika Henzinger , Satish Rao , Di Wang

We present the first work-optimal polylogarithmic-depth parallel algorithm for the minimum cut problem on non-sparse graphs. For $m\geq n^{1+\epsilon}$ for any constant $\epsilon>0$, our algorithm requires $O(m \log n)$ work and $O(\log^3…

Data Structures and Algorithms · Computer Science 2021-02-19 Andrés López-Martínez , Sagnik Mukhopadhyay , Danupon Nanongkai

We present an algorithm that given a linear program with $n$ variables, $m$ constraints, and constraint matrix $A$, computes an $\epsilon$-approximate solution in $\tilde{O}(\sqrt{rank(A)}\log(1/\epsilon))$ iterations with high probability.…

Data Structures and Algorithms · Computer Science 2020-09-02 Yin Tat Lee , Aaron Sidford

We give near-tight lower bounds for the sparsity required in several dimensionality reducing linear maps. First, consider the JL lemma which states that for any set of n vectors in R there is a matrix A in R^{m x d} with m = O(eps^{-2}log…

Data Structures and Algorithms · Computer Science 2012-11-07 Jelani Nelson , Huy L. Nguyen

Let $E, F, E_0$ be Banach spaces, with $E_0$ a subspace of $E$. For a maximal Banach operator ideal $\mathcal{A}$, we show that a linear operator from $E_0$ to $F$ can be extended to a linear operator from $E$ to $F$ that belongs to…

Functional Analysis · Mathematics 2025-06-19 Nahuel Albarracín , Pablo Turco

We introduce the sparse operator compression to compress a self-adjoint higher-order elliptic operator with rough coefficients and various boundary conditions. The operator compression is achieved by using localized basis functions, which…

Numerical Analysis · Mathematics 2017-08-10 Thomas Y. Hou , Pengchuan Zhang

There has been a surge of interest in spectral hypergraph sparsification, a natural generalization of spectral sparsification for graphs. In this paper, we present a simple fully dynamic algorithm for maintaining spectral hypergraph…

Data Structures and Algorithms · Computer Science 2026-01-12 Sebastian Forster , Gramoz Goranci , Ali Momeni

In this paper, we introduce a variant of spectral sparsification, called probabilistic $(\varepsilon,\delta)$-spectral sparsification. Roughly speaking, it preserves the cut value of any cut $(S,S^{c})$ with an $1\pm\varepsilon$…

Data Structures and Algorithms · Computer Science 2014-01-03 Yin Tat Lee

We develop and analyze stochastic optimization algorithms for problems in which the expected loss is strongly convex, and the optimum is (approximately) sparse. Previous approaches are able to exploit only one of these two structures,…

Machine Learning · Statistics 2012-07-19 Alekh Agarwal , Sahand Negahban , Martin J. Wainwright

We give an algorithm to find a minimum cut in an edge-weighted directed graph with $n$ vertices and $m$ edges in $\tilde O(n\cdot \max(m^{2/3}, n))$ time. This improves on the 30 year old bound of $\tilde O(nm)$ obtained by Hao and Orlin…

Data Structures and Algorithms · Computer Science 2021-11-18 Ruoxu Cen , Jason Li , Danupon Nanongkai , Debmalya Panigrahi , Kent Quanrud , Thatchaphol Saranurak

We develop a new parallel algorithm for minimizing Lipschitz, convex functions with a stochastic subgradient oracle. The total number of queries made and the query depth, i.e., the number of parallel rounds of queries, match the prior…

Optimization and Control · Mathematics 2024-06-12 Arun Jambulapati , Aaron Sidford , Kevin Tian

Good approximations have been attained for the sparsest cut problem by rounding solutions to convex relaxations via low-distortion metric embeddings. Recently, Bryant and Tupper showed that this approach extends to the hypergraph setting by…

Data Structures and Algorithms · Computer Science 2023-03-09 Adam D. Jozefiak , F. Bruce Shepherd

In a capacitated directed graph, it is known that the set of all min-cuts forms a distributive lattice [1], [2]. Here, we describe this lattice as a regular predicate whose forbidden elements can be advanced in constant parallel time after…

Data Structures and Algorithms · Computer Science 2025-12-23 Robert Streit , Vijay K. Garg

Motivated by the notion of K-gentle partition of unity introduced in [12] and the notion of K-Lipschitz retract studied in [17], we study a weaker notion related to the Kantorovich-Rubinstein transport distance, that we call K-random…

Functional Analysis · Mathematics 2016-09-07 Luigi Ambrosio , Daniele Puglisi

We study extension theorems for Lipschitz-type operators acting on metric spaces and with values on spaces of integrable functions. Pointwise domination is not a natural feature of such spaces, and so almost everywhere inequalities and…

Functional Analysis · Mathematics 2019-10-02 W. V. Cavalcante , P. Rueda , E. A. Sánchez-Pérez

Given sparse collections of measurable sets $\mathcal S_k$, $k=1,2,\ldots ,N$, in a general measure space $(X,\mathfrak M,\mu)$, let $ \Lambda_{\mathcal S_k}$ be the sparse operator, corresponding to $\mathcal S_k$. We show that the maximal…

Classical Analysis and ODEs · Mathematics 2021-01-26 Grigori A. Karagulyan , Michael T. Lacey

We prove that the size of the sparsest directed k-spanner of a graph can be approximated in polynomial time to within a factor of $\tilde{O}(\sqrt{n})$, for all k >= 3. This improves the $\tilde{O}(n^{2/3})$-approximation recently shown by…

Data Structures and Algorithms · Computer Science 2010-12-21 Arnab Bhattacharyya , Konstantin Makarychev

We present a randomized augmenting paths-based algorithm to compute the maximum flow in a directed, uncapacitated graph in almost $m+nF$ time, matching the algorithm of Karger and Levine for undirected graphs (SICOMP 2015). Combined with an…

Data Structures and Algorithms · Computer Science 2026-04-17 Jason Li

In this paper we study the problem of minimizing a submodular function $f : 2^V \rightarrow \mathbb{R}$ that is guaranteed to have a $k$-sparse minimizer. We give a deterministic algorithm that computes an additive $\epsilon$-approximate…

Data Structures and Algorithms · Computer Science 2024-07-09 Andrei Graur , Haotian Jiang , Aaron Sidford

We present an algorithm for computing $s$-$t$ maximum flows in directed graphs in $\widetilde{O}(m^{4/3+o(1)}U^{1/3})$ time. Our algorithm is inspired by potential reduction interior point methods for linear programming. Instead of using…

Data Structures and Algorithms · Computer Science 2020-09-08 Tarun Kathuria
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