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We present the first algorithm to morph graphs on the torus. Given two isotopic essentially 3-connected embeddings of the same graph on the Euclidean flat torus, where the edges in both drawings are geodesics, our algorithm computes a…

Computational Geometry · Computer Science 2020-07-17 Erin Wolf Chambers , Jeff Erickson , Patrick Lin , Salman Parsa

An integer adder for integers in the binary representation is one of the basic operations of any digital processor. For adding two integers of N bits each, the serial adder takes as many clock ticks. For achieving higher speeds, parallel…

Hardware Architecture · Computer Science 2019-03-26 Duggirala Meher Krishna , Duggirala Ravi

Automated design of neural network architectures tailored for a specific task is an extremely promising, albeit inherently difficult, avenue to explore. While most results in this domain have been achieved on image classification and…

Computer Vision and Pattern Recognition · Computer Science 2019-05-20 Vladimir Nekrasov , Hao Chen , Chunhua Shen , Ian Reid

Radar sensors offer power-efficient solutions for always-on smart devices, but processing the data streams on resource-constrained embedded platforms remains challenging. This paper presents novel techniques that leverage the temporal…

Machine Learning · Computer Science 2023-09-13 Max Sponner , Julius Ott , Lorenzo Servadei , Bernd Waschneck , Robert Wille , Akash Kumar

Subgraph counting aims to count the number of occurrences of a subgraph T (aka as a template) in a given graph G. The basic problem has found applications in diverse domains. The problem is known to be computationally challenging - the…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-27 Langshi Chen , Bo Peng , Sabra Ossen , Anil Vullikanti , Madhav Marathe , Lei Jiang , Judy Qiu

Graph embeddings play a critical role in graph representation learning, allowing machine learning models to explore and interpret graph-structured data. However, existing methods often rely on opaque, high-dimensional embeddings, limiting…

Machine Learning · Computer Science 2025-11-26 Astrit Tola , Funmilola Mary Taiwo , Cuneyt Gurcan Akcora , Baris Coskunuzer

Recently, there have been some breakthroughs in graph analysis by applying the graph neural networks (GNNs) following a neighborhood aggregation scheme, which demonstrate outstanding performance in many tasks. However, we observe that the…

Machine Learning · Computer Science 2021-04-13 Hanchen Wang , Defu Lian , Ying Zhang , Lu Qin , Xiangjian He , Yiguang Lin , Xuemin Lin

The Graph Convolutional Network (GCN) model and its variants are powerful graph embedding tools for facilitating classification and clustering on graphs. However, a major challenge is to reduce the complexity of layered GCNs and make them…

Machine Learning · Computer Science 2020-08-06 Hanqing Zeng , Hongkuan Zhou , Ajitesh Srivastava , Rajgopal Kannan , Viktor Prasanna

For $p,q\ge2$ the $\{p,q\}$-tiling graph is the (finite or infinite) planar graph $T_{p,q}$ where all faces are cycles of length $p$ and all vertices have degree $q$. We give algorithms for the problem of recognizing (induced) subgraphs of…

Computational Geometry · Computer Science 2026-03-09 Eliel Ingervo , Sándor Kisfaludi-Bak

In recent years, graph representation learning has gained significant popularity, which aims to generate node embeddings that capture features of graphs. One of the methods to achieve this is employing a technique called random walks that…

Machine Learning · Computer Science 2022-10-13 Deniz Gurevin , Mohsin Shan , Tong Geng , Weiwen Jiang , Caiwen Ding , Omer Khan

In many Multimedia content analytics frameworks feature likelihood maps represented as histograms play a critical role in the overall algorithm. Integral histograms provide an efficient computational framework for extracting multi-scale…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-07 Mahdieh Poostchi , Kannappan Palaniappan , Da Li , Michela Becchi , Filiz Bunyak , Guna Seetharaman

Two-dimensional constrained coding is a problem that is much more difficult than its one-dimensional counterpart. Indeed, in two dimensions, obtaining the answers to very natural questions becomes uncomputable. In particular, it is…

Signal Processing · Electrical Eng. & Systems 2019-04-17 Danny Dubé

We propose a fast methodology for encoding graphs with information-theoretically minimum numbers of bits. Specifically, a graph with property pi is called a pi-graph. If pi satisfies certain properties, then an n-node m-edge pi-graph G can…

Data Structures and Algorithms · Computer Science 2007-05-23 Xin He , Ming-Yang Kao , Hsueh-I Lu

A simultaneous embedding with fixed edges (SEFE) of two planar graphs $R$ and $B$ is a pair of plane drawings of $R$ and $B$ that coincide when restricted to the common vertices and edges of $R$ and $B$. We show that whenever $R$ and $B$…

Computational Geometry · Computer Science 2015-09-01 Fabrizio Frati , Michael Hoffmann , Vincent Kusters

We investigate the complexity of counting Eulerian tours ({\sc #ET}) and its variations from two perspectives---the complexity of exact counting and the complexity w.r.t. approximation-preserving reductions (AP-reductions \cite{MR2044886}).…

Computational Complexity · Computer Science 2010-09-28 Qi Ge , Daniel Stefankovic

Triangles are the basic substructure of networks and triangle counting (TC) has been a fundamental graph computing problem in numerous fields such as social network analysis. Nevertheless, like other graph computing problems, due to the…

Hardware Architecture · Computer Science 2021-12-02 Xueyan Wang , Jianlei Yang , Yinglin Zhao , Xiaotao Jia , Rong Yin , Xuhang Chen , Gang Qu , Weisheng Zhao

Limited by the time complexity of querying k-hop neighbors in a graph database, most graph algorithms cannot be deployed online and execute millisecond-level inference. This problem dramatically limits the potential of applying graph…

Artificial Intelligence · Computer Science 2021-07-06 Xuhong Wang , Ding Lyu , Mengjian Li , Yang Xia , Qi Yang , Xinwen Wang , Xinguang Wang , Ping Cui , Yupu Yang , Bowen Sun , Zhenyu Guo

Biconnectivity is one of the most fundamental graph problems. The canonical parallel biconnectivity algorithm is the Tarjan-Vishkin algorithm, which has $O(n+m)$ optimal work (number of operations) and polylogarithmic span (longest…

Data Structures and Algorithms · Computer Science 2026-01-21 Xiaojun Dong , Letong Wang , Yan Gu , Yihan Sun

UMAP is a non-parametric graph-based dimensionality reduction algorithm using applied Riemannian geometry and algebraic topology to find low-dimensional embeddings of structured data. The UMAP algorithm consists of two steps: (1) Compute a…

Machine Learning · Computer Science 2021-08-31 Tim Sainburg , Leland McInnes , Timothy Q Gentner

A (possibly denerate) drawing of a graph $G$ in the plane is approximable by an embedding if it can be turned into an embedding by an arbitrarily small perturbation. We show that testing, whether a straight-line drawing of a planar graph…

Computational Geometry · Computer Science 2017-05-09 Radoslav Fulek