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Graph-based machine learning has seen an increased interest over the last decade with many connections to other fields of applied mathematics. Learning based on partial differential equations, such as the phase-field Allen-Cahn equation,…

Numerical Analysis · Mathematics 2025-12-23 Chiara Faccio , Margherita Porcelli , Francesco Rinaldi , Martin Stoll

This paper focuses on a significant yet challenging task: out-of-distribution detection (OOD detection), which aims to distinguish and reject test samples with semantic shifts, so as to prevent models trained on in-distribution (ID) data…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Xiang Fang , Arvind Easwaran , Blaise Genest , Ponnuthurai Nagaratnam Suganthan

Reconstructing components of a genomic mixture from data obtained by means of DNA sequencing is a challenging problem encountered in a variety of applications including single individual haplotyping and studies of viral communities.…

Genomics · Quantitative Biology 2019-11-14 Ziqi Ke , Haris Vikalo

Let $m(n,r)$ denote the minimal number of edges in an $n$-uniform hypergraph which is not $r$-colorable. For the broad history of the problem see [RaiSh]. It is known that for a fixed $n$ the sequence \[ \frac{m(n,r)}{r^n} \] has a limit.…

Combinatorics · Mathematics 2019-07-12 Danila Cherkashin

We revisit the algorithmic problem of finding a triangle in a graph: We give a randomized combinatorial algorithm for triangle detection in a given $n$-vertex graph with $m$ edges running in $O(n^{7/3})$ time, or alternatively in…

Data Structures and Algorithms · Computer Science 2024-03-08 Adrian Dumitrescu

Hypergraph data, which capture multi-way interactions among entities, are increasingly prevalent in the big data era. Generating new hyperlinks from an observed, usually high-dimensional hypergraph is an important yet challenging task with…

Methodology · Statistics 2026-05-14 Shihao Wu , Junyi Yang , Gongjun Xu , Ji Zhu

This work presents a novel trie (prefix-tree)-based parallel decoding method that addresses the memory inefficiency of batch-based beam search. By sharing a single KV cache across beams with common prefixes, our approach dramatically…

Computation and Language · Computer Science 2025-09-23 Brian J Chan , MaoXun Huang , Jui-Hung Cheng , Chao-Ting Chen , Hen-Hsen Huang

Dense subgraph discovery aims to find a dense component in edge-weighted graphs. This is a fundamental graph-mining task with a variety of applications and thus has received much attention recently. Although most existing methods assume…

Machine Learning · Computer Science 2020-06-25 Yuko Kuroki , Atsushi Miyauchi , Junya Honda , Masashi Sugiyama

We consider the problem of finding a large clique in an Erd\H{o}s--R\'enyi random graph where we are allowed unbounded computational time but can only query a limited number of edges. Recall that the largest clique in $G \sim G(n,1/2)$ has…

Combinatorics · Mathematics 2024-07-12 Endre Csóka , András Pongrácz

We demonstrate that the best $k$-sparse approximation of a length-$n$ vector can be recovered within a $(1+\epsilon)$-factor approximation in $O((k/\epsilon) \log n)$ time using a non-adaptive linear sketch with $O((k/\epsilon) \log n)$…

Data Structures and Algorithms · Computer Science 2025-10-24 Nick Fischer , Vasileios Nakos

This paper examines a model involving two dynamic Erd\H{o}s-R\'enyi random graphs that evolve in parallel, with edges in each graph alternating between being present and absent according to specified on- and off-time distributions. A key…

Probability · Mathematics 2025-05-27 Michel Mandjes , Jiesen Wang

Can we use machine learning to compress graph data? The absence of ordering in graphs poses a significant challenge to conventional compression algorithms, limiting their attainable gains as well as their ability to discover relevant…

Machine Learning · Computer Science 2023-09-26 Giorgos Bouritsas , Andreas Loukas , Nikolaos Karalias , Michael M. Bronstein

In this paper, we investigate the problem of recovering source information from an incomplete set of network coded data. We first study the theoretical performance of such systems under maximum a posteriori (MAP) decoding and derive the…

Information Theory · Computer Science 2015-03-16 Eirina Bourtsoulatze , Nikolaos Thomos , Pascal Frossard

For $n\geq 3$, let $r=r(n)\geq 3$ be an integer. A hypergraph is $r$-uniform if each edge is a set of $r$ vertices, and is said to be linear if two edges intersect in at most one vertex. In this paper, the number of linear $r$-uniform…

Combinatorics · Mathematics 2019-08-20 Brendan D. McKay , Fang Tian

In the search for highly efficient decoders for short LDPC codes approaching maximum likelihood performance, a relayed decoding strategy, specifically activating the ordered statistics decoding process upon failure of a neural min-sum…

Information Theory · Computer Science 2024-03-26 Guangwen Li , Xiao Yu

We give the first almost-linear time algorithm for computing the \emph{maximal $k$-edge-connected subgraphs} of an undirected unweighted graph for any constant $k$. More specifically, given an $n$-vertex $m$-edge graph $G=(V,E)$ and a…

Data Structures and Algorithms · Computer Science 2023-07-04 Thatchaphol Saranurak , Wuwei Yuan

We study the edge-coloring problem in simple $n$-vertex $m$-edge graphs with maximum degree $\Delta$. This is one of the most classical and fundamental graph-algorithmic problems. Vizing's celebrated theorem provides…

Data Structures and Algorithms · Computer Science 2024-07-10 Michael Elkin , Ariel Khuzman

Recent papers initiated the study of a generalization of group testing where the potentially contaminated sets are the members of a given hypergraph F=(V,E). This generalization finds application in contexts where contaminations can be…

Data Structures and Algorithms · Computer Science 2024-07-02 Annalisa De Bonis

We present a new algorithm for finding large independent sets in $3$-colorable graphs with small $1$-sided threshold rank. Specifically, given an $n$-vertex $3$-colorable graph whose uniform random walk matrix has at most $r$ eigenvalues…

Data Structures and Algorithms · Computer Science 2025-08-06 Jun-Ting Hsieh

We give nearly optimal bounds on the sample complexity of $(\widetilde{\Omega}(\epsilon),\epsilon)$-tolerant testing the $\rho$-independent set property in the dense graph setting. In particular, we give an algorithm that inspects a random…

Data Structures and Algorithms · Computer Science 2025-03-28 Cameron Seth
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