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Related papers: Sublinear Algorithms for $(1.5+\epsilon)$-Approxim…

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Subset Sum Ratio is the following optimization problem: Given a set of $n$ positive numbers $I$, find disjoint subsets $X,Y \subseteq I$ minimizing the ratio $\max\{\Sigma(X)/\Sigma(Y),\Sigma(Y)/\Sigma(X)\}$, where $\Sigma(Z)$ denotes the…

Data Structures and Algorithms · Computer Science 2023-10-12 Karl Bringmann

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 present a simple deterministic single-pass $(2+\epsilon)$-approximation algorithm for the maximum weight matching problem in the semi-streaming model. This improves upon the currently best known approximation ratio of $(4+\epsilon)$. Our…

Data Structures and Algorithms · Computer Science 2018-11-07 Ami Paz , Gregory Schwartzman

We provide the currently fastest randomized (1+epsilon)-approximation algorithm for the closest vector problem in the infinity norm. The running time of our method depends on the dimension n and the approximation guarantee epsilon by 2^O(n)…

Data Structures and Algorithms · Computer Science 2010-12-13 Friedrich Eisenbrand , Nicolai Hähnle , Martin Niemeier

We give the first almost-linear time algorithm for computing the \emph{maximal $k$-edge-connected subgraphs} of an undirected unweighted graph for any constant $k$. More specifically, given an $n$-vertex $m$-edge graph $G=(V,E)$ and a…

Data Structures and Algorithms · Computer Science 2023-07-04 Thatchaphol Saranurak , Wuwei Yuan

We study polynomial-time approximation algorithms for (edge/vertex) Sparsest Cut and Small Set Expansion in terms of $k$, the number of edges or vertices cut in the optimal solution. Our main results are $\mathcal{O}(\text{polylog}\,…

Data Structures and Algorithms · Computer Science 2024-03-15 Aditya Anand , Euiwoong Lee , Jason Li , Thatchaphol Saranurak

The problem of sparsifying a graph or a hypergraph while approximately preserving its cut structure has been extensively studied and has many applications. In a seminal work, Bencz\'ur and Karger (1996) showed that given any $n$-vertex…

Data Structures and Algorithms · Computer Science 2021-06-22 Yu Chen , Sanjeev Khanna , Ansh Nagda

We present an optimal, combinatorial 1-1/e approximation algorithm for monotone submodular optimization over a matroid constraint. Compared to the continuous greedy algorithm (Calinescu, Chekuri, Pal and Vondrak, 2008), our algorithm is…

Data Structures and Algorithms · Computer Science 2013-11-20 Yuval Filmus , Justin Ward

Constrained submodular maximization problems encompass a wide variety of applications, including personalized recommendation, team formation, and revenue maximization via viral marketing. The massive instances occurring in modern day…

Data Structures and Algorithms · Computer Science 2024-02-20 Georgios Amanatidis , Federico Fusco , Philip Lazos , Stefano Leonardi , Rebecca Reiffenhäuser

In this paper, we revisit the classic approximate All-Pairs Shortest Paths (APSP) problem in undirected graphs. For unweighted graphs, we provide an algorithm for $2$-approximate APSP in $\tilde O(n^{2.5-r}+n^{\omega(r)})$ time, for any…

Data Structures and Algorithms · Computer Science 2023-10-31 Michal Dory , Sebastian Forster , Yael Kirkpatrick , Yasamin Nazari , Virginia Vassilevska Williams , Tijn de Vos

We prove that any semi-streaming algorithm for $(1-\epsilon)$-approximation of maximum bipartite matching requires \[ \Omega(\frac{\log{(1/\epsilon)}}{{\log{(1/\beta)}}}) \] passes, where $\beta \in (0,1)$ is the largest parameter so that…

Data Structures and Algorithms · Computer Science 2023-10-12 Sepehr Assadi , Janani Sundaresan

We present combinatorial and parallelizable algorithms for maximization of a submodular function, not necessarily monotone, with respect to a size constraint. We improve the best approximation factor achieved by an algorithm that has…

Data Structures and Algorithms · Computer Science 2024-02-21 Yixin Chen , Alan Kuhnle

We introduce the notion of {\em fair cuts} as an approach to leverage approximate $(s,t)$-mincut (equivalently $(s,t)$-maxflow) algorithms in undirected graphs to obtain near-linear time approximation algorithms for several cut problems.…

Data Structures and Algorithms · Computer Science 2023-01-13 Jason Li , Danupon Nanongkai , Debmalya Panigrahi , Thatchaphol Saranurak

We present an $\tilde O(m+n^{1.5})$-time randomized algorithm for maximum cardinality bipartite matching and related problems (e.g. transshipment, negative-weight shortest paths, and optimal transport) on $m$-edge, $n$-node graphs. For…

Data Structures and Algorithms · Computer Science 2021-10-15 Jan van den Brand , Yin-Tat Lee , Danupon Nanongkai , Richard Peng , Thatchaphol Saranurak , Aaron Sidford , Zhao Song , Di Wang

We study the maximum weight matching problem in the random-order semi-streaming model and in the robust communication model. Unlike many other sublinear models, in these two frameworks, there is a large gap between the guarantees of the…

Data Structures and Algorithms · Computer Science 2024-08-29 Diba Hashemi , Weronika Wrzos-Kaminska

We present a new approximation algorithm for the minimum 2-edge-connected spanning subgraph problem. Its approximation ratio is $\frac{4}{3}$, which matches the current best ratio. The approximation ratio of the algorithm is $\frac{6}{5}$…

Data Structures and Algorithms · Computer Science 2023-05-10 Ali Çivril

Finding the length of the longest increasing subsequence (LIS) is a classic algorithmic problem. Let $n$ denote the size of the array. Simple $O(n\log n)$ algorithms are known for this problem. We develop a polylogarithmic time randomized…

Data Structures and Algorithms · Computer Science 2013-08-06 M. Saks , C. Seshadhri

In this paper, we consider the unconstrained submodular maximization problem. We propose the first algorithm for this problem that achieves a tight $(1/2-\varepsilon)$-approximation guarantee using $\tilde{O}(\varepsilon^{-1})$ adaptive…

Data Structures and Algorithms · Computer Science 2018-11-20 Lin Chen , Moran Feldman , Amin Karbasi

The {\em maximum cardinality} and {\em maximum weight matching} problems can be solved in time $\tilde{O}(m\sqrt{n})$, a bound that has resisted improvement despite decades of research. (Here $m$ and $n$ are the number of edges and…

Data Structures and Algorithms · Computer Science 2011-12-06 Ran Duan , Seth Pettie , Hsin-Hao Su

We introduce efficient $(1+\varepsilon)$-approximation algorithms for the binary matrix factorization (BMF) problem, where the inputs are a matrix $\mathbf{A}\in\{0,1\}^{n\times d}$, a rank parameter $k>0$, as well as an accuracy parameter…

Data Structures and Algorithms · Computer Science 2023-06-06 Ameya Velingker , Maximilian Vötsch , David P. Woodruff , Samson Zhou