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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

Vertex hunting (VH) is the task of estimating a simplex from noisy data points and has many applications in areas such as network and text analysis. We introduce a new variant, semi-supervised vertex hunting (SSVH), in which partial…

Methodology · Statistics 2025-10-28 Yicong Jiang , Zheng Tracy Ke

We study the problem of sketching an input graph, so that given the sketch, one can estimate the weight of any cut in the graph within factor $1+\epsilon$. We present lower and upper bounds on the size of a randomized sketch, focusing on…

Data Structures and Algorithms · Computer Science 2014-11-11 Alexandr Andoni , Robert Krauthgamer , David P. Woodruff

Visual similarities discovery (VSD) is an important task with broad e-commerce applications. Given an image of a certain object, the goal of VSD is to retrieve images of different objects with high perceptual visual similarity. Although…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Oren Barkan , Tal Reiss , Jonathan Weill , Ori Katz , Roy Hirsch , Itzik Malkiel , Noam Koenigstein

Dynamic connectivity is a fundamental dynamic graph problem, and recent algorithmic breakthroughs on dynamic graph sketching have reshaped what is theoretically possible: by encoding the graph as per-vertex linear sketches, these algorithms…

Data Structures and Algorithms · Computer Science 2026-05-15 Quinten De Man , Gilvir Gill , Michael A. Bender , Laxman Dhulipala , David Tench

In this paper we present the Markov variation, a smoothness measure which offers a probabilistic interpretation of graph signal smoothness. This measure is then used to develop an optimization framework for graph signal interpolation. Our…

Signal Processing · Electrical Eng. & Systems 2020-01-29 Ayelet Heimowitz , Yonina C. Eldar

Random walk neural networks (RWNNs) have emerged as a promising approach for graph representation learning, leveraging recent advances in sequence models to process random walks. However, under realistic sampling constraints, RWNNs often…

Machine Learning · Computer Science 2025-10-28 Michael Ito , Danai Koutra , Jenna Wiens

Anomaly detection in dynamic graphs is essential for identifying malicious activities, fraud, and unexpected behaviors in real-world systems such as cybersecurity and power grids. However, existing approaches struggle with scalability,…

Machine Learning · Computer Science 2025-09-16 Ocheme Anthony Ekle , William Eberle

Structural balance theory studies stability in networks. Given a $n$-vertex complete graph $G=(V,E)$ whose edges are labeled positive or negative, the graph is considered \emph{balanced} if every triangle either consists of three positive…

Data Structures and Algorithms · Computer Science 2023-06-02 Vikrant Ashvinkumar , Sepehr Assadi , Chengyuan Deng , Jie Gao , Chen Wang

The mincut graph bisection problem involves partitioning the n vertices of a graph into disjoint subsets, each containing exactly n/2 vertices, while minimizing the number of "cut" edges with an endpoint in each subset. When considered over…

Statistical Mechanics · Physics 2010-04-27 Allon G. Percus , Gabriel Istrate , Bruno Goncalves , Robert Z. Sumi , Stefan Boettcher

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

Vector data is prevalent across business and scientific applications, and its popularity is growing with the proliferation of learned embeddings. Vector data collections often reach billions of vectors with thousands of dimensions, thus,…

Information Retrieval · Computer Science 2025-09-09 Ilias Azizi , Karima Echihab , Themis Palpanas , Vassilis Christophides

Graph learning has emerged as a promising technique for multi-view clustering with its ability to learn a unified and robust graph from multiple views. However, existing graph learning methods mostly focus on the multi-view consistency…

Machine Learning · Computer Science 2021-07-06 Youwei Liang , Dong Huang , Chang-Dong Wang , Philip S. Yu

Equivariant Graph Neural Networks (GNNs) have achieved remarkable success across diverse scientific applications. However, existing approaches face critical efficiency challenges when scaling to large geometric graphs and suffer significant…

Machine Learning · Computer Science 2025-06-25 Yuelin Zhang , Jiacheng Cen , Jiaqi Han , Wenbing Huang

Which one is better between two representative graph summarization models with and without edge weights? From web graphs to online social networks, large graphs are everywhere. Graph summarization, which is an effective graph compression…

Databases · Computer Science 2022-05-09 Shinhwan Kang , Kyuhan Lee , Kijung Shin

We consider extension variants of the classical graph problems Vertex Cover and Independent Set. Given a graph $G=(V,E)$ and a vertex set $U \subseteq V$, it is asked if there exists a minimal vertex cover (resp.\ maximal independent set)…

Computational Complexity · Computer Science 2018-10-12 Katrin Casel , Henning Fernau , Mehdi Khosravian Ghadikolaei , Jérôme Monnot , Florian Sikora

This work develops a flexible and mathematically sound framework for the design and analysis of graph scattering networks with variable branching ratios and generic functional calculus filters. Spectrally-agnostic stability guarantees for…

Machine Learning · Computer Science 2023-01-30 Christian Koke , Gitta Kutyniok

By definition, a rigid graph in $\mathbb{R}^d$ (or on a sphere) has a finite number of embeddings up to rigid motions for a given set of edge length constraints. These embeddings are related to the real solutions of an algebraic system.…

Combinatorics · Mathematics 2021-10-26 Evangelos Bartzos , Ioannis Z. Emiris , Raimundas Vidunas

A path query extracts vertex tuples from a labeled graph, based on the words that are formed by the paths connecting the vertices. We study the computational complexity of measuring the contribution of edges and vertices to an answer to a…

Databases · Computer Science 2022-12-16 Majd Khalil , Benny Kimelfeld

Unrolled computation graphs arise in many scenarios, including training RNNs, tuning hyperparameters through unrolled optimization, and training learned optimizers. Current approaches to optimizing parameters in such computation graphs…

Machine Learning · Computer Science 2021-12-28 Paul Vicol , Luke Metz , Jascha Sohl-Dickstein
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