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Graph search, the process of visiting vertices in a graph in a specific order, has demonstrated magical powers in many important algorithms. But a systematic study was only initiated by Corneil et al.~a decade ago, and only by then we…

Data Structures and Algorithms · Computer Science 2019-05-24 Yixin Cao , Guozhen Rong , Jianxin Wang , Zhifeng Wang

Finding a maximum-cardinality or maximum-weight matching in (edge-weighted) undirected graphs is among the most prominent problems of algorithmic graph theory. For $n$-vertex and $m$-edge graphs, the best known algorithms run in…

Data Structures and Algorithms · Computer Science 2021-05-10 Tomohiro Koana , Viatcheslav Korenwein , André Nichterlein , Rolf Niedermeier , Philipp Zschoche

Minimum Spanning Trees are a well-studied subset of graph problems. While classical algorithms have existed to solve these problems for decades, new variations and application areas are constantly being discovered. When dealing with large…

Data Structures and Algorithms · Computer Science 2023-12-29 Arjun Bhalla

We propose a randomized greedy search algorithm to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. Given the large size and awkward discrete nature of the search space, the…

Methodology · Statistics 2021-05-11 David B. Dahl , Devin J. Johnson , Peter Mueller

We revisit a classical graph-theoretic problem, the \textit{single-source shortest-path} (SSSP) problem, in weighted unit-disk graphs. We first propose an exact (and deterministic) algorithm which solves the problem in $O(n \log^2 n)$ time…

Computational Geometry · Computer Science 2019-03-14 Haitao Wang , Jie Xue

Frequent Subgraph Mining (FSM) is the key task in many graph mining and machine learning applications. Numerous systems have been proposed for FSM in the past decade. Although these systems show good performance for small patterns (with no…

Databases · Computer Science 2021-02-09 Peng Jiang , Rujia Wang , Bo Wu

Recently, differentiable search methods have made major progress in reducing the computational costs of neural architecture search. However, these approaches often report lower accuracy in evaluating the searched architecture or…

Computer Vision and Pattern Recognition · Computer Science 2019-04-30 Xin Chen , Lingxi Xie , Jun Wu , Qi Tian

We present an approach to implement binary search trees in the rule-based graph programming language GP 2. Our implementation uses GP 2's rooted graph transformation rules to be fast and supports insertion, deletion and query operations. We…

Programming Languages · Computer Science 2026-01-08 Ziad Ismaili Alaoui , Detlef Plump

We consider the performance of the Depth First Search (DFS) algorithm on the random graph $G\left(n,\frac{1+\epsilon}{n}\right)$, $\epsilon>0$ a small constant. Recently, Enriquez, Faraud and M\'enard [2] proved that the stack $U$ of the…

Combinatorics · Mathematics 2022-07-27 Sahar Diskin , Michael Krivelevich

We study dynamic graph algorithms in the Massively Parallel Computation model, which was inspired by practical data processing systems. Our goal is to provide algorithms that can efficiently handle large batches of edge insertions and…

Data Structures and Algorithms · Computer Science 2021-01-12 Krzysztof Nowicki , Krzysztof Onak

Modern day computing increasingly relies on specialization to satiate growing performance and efficiency requirements. A core challenge in designing such specialized hardware architectures is how to perform mapping space search, i.e.,…

Machine Learning · Computer Science 2021-03-03 Kartik Hegde , Po-An Tsai , Sitao Huang , Vikas Chandra , Angshuman Parashar , Christopher W. Fletcher

In this note, we give an algorithm that computes the linearwidth of input $n$-vertex graphs in time $O^*(2^n)$, which improves a trivial $O^*(2^m)$-time algorithm, where $n$ and $m$ the number of vertices and edges, respectively.

Data Structures and Algorithms · Computer Science 2021-03-08 Yasuaki Kobayashi , Yu Nakahata

We propose a space-efficient algorithm for hidden surface removal that combines one of the fastest previous algorithms for that problem with techniques based on bit manipulation. Such techniques had been successfully used in other settings,…

Computational Geometry · Computer Science 2017-01-10 Frank Kammer , Maarten Löffler , Rodrigo I. Silveira

Sorting and binary searching a dense array can be considered the simplest and most space efficient form of indexing. This holds especially on GPUs as they exhibit exceptional sorting performance. However, the popular opinion is that such a…

Databases · Computer Science 2026-02-24 Justus Henneberg , Felix Schuhknecht

Reachability is the problem of deciding whether there is a path from one vertex to the other in the graph. Standard graph traversal algorithms such as DFS and BFS take linear time to decide reachability however their space complexity is…

Computational Complexity · Computer Science 2019-02-06 Rahul Jain , Raghunath Tewari

Evolving graphs arise in problems where interrelations between data change over time. We present a breadth first search (BFS) algorithm for evolving graphs that computes the most direct influences between nodes at two different times. Using…

Social and Information Networks · Computer Science 2016-03-07 Jiahao Chen , Weijian Zhang

Approximate Nearest Neighbor Search (ANNS) is a core primitive in modern AI systems, and graph-based methods currently offer the best accuracy-efficiency trade-off at scale. The workload is fundamentally memory-bound: graph traversal…

Hardware Architecture · Computer Science 2026-05-26 Sitian Chen , Yusen Li , Yao Chen , Minwen Deng , Jintao Meng , Amelie Chi Zhou

Similarity search approaches based on graph walks have recently attained outstanding speed-accuracy trade-offs, taking aside the memory requirements. In this paper, we revisit these approaches by considering, additionally, the memory…

Computer Vision and Pattern Recognition · Computer Science 2018-06-07 Matthijs Douze , Alexandre Sablayrolles , Hervé Jégou

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

Let G be a plane graph of n nodes, m edges, f faces, and no self-loop. G need not be connected or simple (i.e., free of multiple edges). We give three sets of coding schemes for G which all take O(m+n) time for encoding and decoding. Our…

Data Structures and Algorithms · Computer Science 2007-05-23 Richie Chih-Nan Chuang , Ashim Garg , Xin He , Ming-Yang Kao , Hsueh-I Lu