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In the Any-Angle Pathfinding problem, the goal is to find the shortest path between a pair of vertices on a uniform square grid, that is not constrained to any fixed number of possible directions over the grid. Visibility Graphs are a known…

Computational Geometry · Computer Science 2017-02-07 Shunhao Oh , Hon Wai Leong

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

Let $G = (V,E,w)$ be a weighted undirected graph on $|V| = n$ vertices and $|E| = m$ edges, let $k \ge 1$ be any integer, and let $\epsilon < 1$ be any parameter. We present the following results on fast constructions of spanners with…

Data Structures and Algorithms · Computer Science 2021-08-03 Hung Le , Shay Solomon

The radius and diameter are fundamental graph parameters. They are defined as the minimum and maximum of the eccentricities in a graph, respectively, where the eccentricity of a vertex is the largest distance from the vertex to another…

Data Structures and Algorithms · Computer Science 2015-06-08 Amir Abboud , Virginia Vassilevska Williams , Joshua Wang

Nearest neighbor search and k-nearest neighbor graph construction are two fundamental issues arise from many disciplines such as multimedia information retrieval, data-mining and machine learning. They become more and more imminent given…

Information Retrieval · Computer Science 2020-09-18 Wan-Lei Zhao , Hui Wang , Chong-Wah Ngo

We study the fully dynamic All-Pairs Shortest Paths (APSP) problem in undirected edge-weighted graphs. Given an $n$-vertex graph $G$ with non-negative edge lengths, that undergoes an online sequence of edge insertions and deletions, the…

Data Structures and Algorithms · Computer Science 2023-04-20 Julia Chuzhoy , Ruimin Zhang

Most natural language processing tasks can be formulated as the approximated nearest neighbor search problem, such as word analogy, document similarity, machine translation. Take the question-answering task as an example, given a question…

Artificial Intelligence · Computer Science 2017-08-28 Jing Wang

For a given dataset $\mathcal{D}$ and structured label $f$, the goal of Filtered Approximate Nearest Neighbor Search (FANNS) algorithms is to find top-$k$ points closest to a query that satisfy label constraints, while ensuring both recall…

Databases · Computer Science 2025-09-10 Jiayang Shi , Yuzheng Cai , Weiguo Zheng

Computational complexity and approximation algorithms are reported for a problem of stabbing a set of straight line segments with the least cardinality set of disks of fixed radii $r>0$ where the set of segments forms a straight line…

Computational Geometry · Computer Science 2018-03-23 Konstantin Kobylkin

We introduce and study the problem of balanced districting, where given an undirected graph with vertices carrying two types of weights (different population, resource types, etc) the goal is to maximize the total weights covered in vertex…

Data Structures and Algorithms · Computer Science 2025-06-03 Prathamesh Dharangutte , Jie Gao , Shang-En Huang , Fang-Yi Yu

The significant progress in constructing graph spanners that are sparse (small number of edges) or light (low total weight) has skipped spanners that are everywhere-sparse (small maximum degree). This disparity is in line with other network…

Data Structures and Algorithms · Computer Science 2012-05-02 Eden Chlamtac , Michael Dinitz , Robert Krauthgamer

Graph sparsification is a technique that approximates a given graph by a sparse graph with a subset of vertices and/or edges. The goal of an effective sparsification algorithm is to maintain specific graph properties relevant to the…

Databases · Computer Science 2023-11-22 Yuhan Chen , Haojie Ye , Sanketh Vedula , Alex Bronstein , Ronald Dreslinski , Trevor Mudge , Nishil Talati

This study develops a graph search algorithm to find the optimal discrimination path for the binary classification problem. The objective function is defined as the difference of variations between the true positive (TP) and false positive…

Machine Learning · Computer Science 2024-01-10 Qinwu Xu

We consider the fundamental problem of decomposing a large-scale approximate nearest neighbor search (ANNS) problem into smaller sub-problems. The goal is to partition the input points into neighborhood-preserving shards, so that the…

Data Structures and Algorithms · Computer Science 2024-03-05 Lars Gottesbüren , Laxman Dhulipala , Rajesh Jayaram , Jakub Lacki

In the classical Node-Disjoint Paths (NDP) problem, we are given an $n$-vertex graph $G=(V,E)$, and a collection $M=\{(s_1,t_1),\ldots,(s_k,t_k)\}$ of pairs of its vertices, called source-destination, or demand pairs. The goal is to route…

Data Structures and Algorithms · Computer Science 2017-11-07 Julia Chuzhoy , David H. K. Kim , Rachit Nimavat

The densest subgraph problem has received significant attention, both in theory and in practice, due to its applications in problems such as community detection, social network analysis, and spam detection. Due to the high cost of obtaining…

Data Structures and Algorithms · Computer Science 2023-11-09 Pattara Sukprasert , Quanquan C. Liu , Laxman Dhulipala , Julian Shun

In the decremental single-source shortest paths (SSSP) problem we want to maintain the distances between a given source node $s$ and every other node in an $n$-node $m$-edge graph $G$ undergoing edge deletions. While its static counterpart…

Data Structures and Algorithms · Computer Science 2018-08-20 Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

In the decremental single-source shortest paths (SSSP) problem, the input is an undirected graph $G=(V,E)$ with $n$ vertices and $m$ edges undergoing edge deletions, together with a fixed source vertex $s\in V$. The goal is to maintain a…

Data Structures and Algorithms · Computer Science 2020-09-21 Julia Chuzhoy , Thatchaphol Saranurak

The problem of learning a directed acyclic graph (DAG) up to Markov equivalence is equivalent to the problem of finding a permutation of the variables that induces the sparsest graph. Without additional assumptions, this task is known to be…

Methodology · Statistics 2020-11-10 Chandler Squires , Joshua Amaniampong , Caroline Uhler

In this thesis, we present new techniques to deal with fundamental algorithmic graph problems where graphs are directed and partially dynamic, i.e. undergo either a sequence of edge insertions or deletions: - Single-Source Reachability…

Data Structures and Algorithms · Computer Science 2020-11-30 Maximilian Probst Gutenberg
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