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We present a new distance oracle in the fully dynamic setting: given a weighted undirected graph $G=(V,E)$ with $n$ vertices undergoing both edge insertions and deletions, and an arbitrary parameter $\epsilon$ where $\epsilon\in[1/\log^{c}…

Data Structures and Algorithms · Computer Science 2024-04-12 Bernhard Haeupler , Yaowei Long , Thatchaphol Saranurak

We consider parallel, or low adaptivity, algorithms for submodular function maximization. This line of work was recently initiated by Balkanski and Singer and has already led to several interesting results on the cardinality constraint and…

Data Structures and Algorithms · Computer Science 2018-12-03 Chandra Chekuri , Kent Quanrud

In edge orientations, the goal is usually to orient (direct) the edges of an undirected $n$-vertex graph $G$ such that all out-degrees are bounded. When the graph $G$ is fully dynamic, i.e., admits edge insertions and deletions, we wish to…

Data Structures and Algorithms · Computer Science 2013-12-06 Tsvi Kopelowitz , Robert Krauthgamer , Ely Porat , Shay Solomon

We present the first algorithm for maintaining a maximal independent set (MIS) of a fully dynamic graph---which undergoes both edge insertions and deletions---in polylogarithmic time. Our algorithm is randomized and, per update, takes…

Data Structures and Algorithms · Computer Science 2019-09-10 Soheil Behnezhad , Mahsa Derakhshan , MohammadTaghi Hajiaghayi , Cliff Stein , Madhu Sudan

Many application areas collect unstructured trajectory data. In subtrajectory clustering, one is interested to find patterns in this data using a hybrid combination of segmentation and clustering. We analyze two variants of this problem…

Computational Geometry · Computer Science 2025-04-25 Jacobus Conradi , Anne Driemel

We study dynamic algorithms for the longest increasing subsequence (\textsf{LIS}) problem. A dynamic \textsf{LIS} algorithm maintains a sequence subject to operations of the following form arriving one by one: (i) insert an element, (ii)…

Data Structures and Algorithms · Computer Science 2021-03-11 Tomasz Kociumaka , Saeed Seddighin

We present trade-offs in the incremental and fully dynamic settings to maintian a proper coloring. For any fully dynamic $2$-coloring algorithm, the maximum of the update time, number of recolorings, and query time is $\Omega(\log n)$. We…

Data Structures and Algorithms · Computer Science 2020-02-28 Manas Jyoti Kashyop , N. S. Narayanaswamy , Meghana Nasre , Sai Mohith Potluri

We study the $k$-Submodular Cover ($kSC$) problem, a natural generalization of the classical Submodular Cover problem that arises in artificial intelligence and combinatorial optimization tasks such as influence maximization, resource…

Data Structures and Algorithms · Computer Science 2025-11-04 Hue T. Nguyen , Tan D. Tran , Nguyen Long Giang , Canh V. Pham

We consider dynamic algorithms for maintaining Single-Source Reachability (SSR) and approximate Single-Source Shortest Paths (SSSP) on $n$-node $m$-edge directed graphs under edge deletions (decremental algorithms). The previous fastest…

Data Structures and Algorithms · Computer Science 2018-03-02 Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

We study the dynamic correlation clustering problem with $\textit{adaptive}$ edge label flips. In correlation clustering, we are given a $n$-vertex complete graph whose edges are labeled either $(+)$ or $(-)$, and the goal is to minimize…

Data Structures and Algorithms · Computer Science 2026-02-10 Vladimir Braverman , Prathamesh Dharangutte , Shreyas Pai , Vihan Shah , Chen Wang

We give a fully dynamic algorithm maintaining a $(1-\varepsilon)$-approximate directed densest subgraph in $\tilde{O}(\log^3(n)/\varepsilon^6)$ amortized time or $\tilde{O}(\log^4(n)/\varepsilon^7)$ worst-case time per edge update (where…

Data Structures and Algorithms · Computer Science 2023-12-19 Richard Li , Kent Quanrud

In the distributed backup-placement problem each node of a network has to select one neighbor, such that the maximum number of nodes that make the same selection is minimized. This is a natural relaxation of the perfect matching problem, in…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-19 Leonid Barenboim , Gal Oren

We give the first non-trivial fully dynamic probabilistic tree embedding algorithm for weighted graphs undergoing edge insertions and deletions. We obtain a trade-off between amortized update time and expected stretch against an oblivious…

Data Structures and Algorithms · Computer Science 2020-04-24 Sebastian Forster , Gramoz Goranci , Monika Henzinger

We study the lattice agreement (LA) and atomic snapshot problems in asynchronous message-passing systems where up to $f$ nodes may crash. Our main result is a crash-tolerant atomic snapshot algorithm with \textit{amortized constant round…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-01 Vijay Garg , Saptaparni Kumar , Lewis Tseng , Xiong Zheng

The maximum coverage problem is to select $k$ sets from a collection of sets such that the cardinality of the union of the selected sets is maximized. We consider $(1-1/e-\epsilon)$-approximation algorithms for this NP-hard problem in three…

Data Structures and Algorithms · Computer Science 2024-03-22 Amit Chakrabarti , Andrew McGregor , Anthony Wirth

The greedy algorithm for approximating dominating sets is a simple method that is known to compute an $(\ln n+1)$-approximation of a minimum dominating set on any graph with $n$ vertices. We show that a small modification of the greedy…

Discrete Mathematics · Computer Science 2019-01-18 Sebastian Siebertz

We consider the classic Set Cover problem in the data stream model. For $n$ elements and $m$ sets ($m\geq n$) we give a $O(1/\delta)$-pass algorithm with a strongly sub-linear $\tilde{O}(mn^{\delta})$ space and logarithmic approximation…

Data Structures and Algorithms · Computer Science 2016-05-03 Sariel Har-Peled , Piotr Indyk , Sepideh Mahabadi , Ali Vakilian

In submodular covering problems, we are given a monotone, nonnegative submodular function $f: 2^N \rightarrow\mathbb{R}_+$ and wish to find the min-cost set $S\subseteq N$ such that $f(S)=f(N)$. This captures SetCover when $f$ is a coverage…

Data Structures and Algorithms · Computer Science 2025-10-13 Anupam Gupta , Roie Levin

In fully dynamic graphs, we know how to maintain a 2-approximation of maximum matching extremely fast, that is, in polylogarithmic update time or better. In a sharp contrast and despite extensive studies, all known algorithms that maintain…

Data Structures and Algorithms · Computer Science 2019-11-06 Soheil Behnezhad , Jakub Łącki , Vahab Mirrokni

In the submodular cover problem, we are given a non-negative monotone submodular function $f$ over a ground set $E$ of items, and the goal is to choose a smallest subset $S \subseteq E$ such that $f(S) = Q$ where $Q = f(E)$. In the…

Data Structures and Algorithms · Computer Science 2018-11-01 Arpit Agarwal , Sepehr Assadi , Sanjeev Khanna
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