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Graph reconstruction can efficiently detect the underlying topology of massive networks such as the Internet. Given a query oracle and a set of nodes, the goal is to obtain the edge set by performing as few queries as possible. An algorithm…

Data Structures and Algorithms · Computer Science 2024-07-29 Clara Stegehuis , Lotte Weedage

Suppose a graph $G$ is stochastically created by uniformly sampling vertices along a line segment and connecting each pair of vertices with a probability that is a known decreasing function of their distance. We ask if it is possible to…

Data Structures and Algorithms · Computer Science 2020-06-09 Yu Chen , Sampath Kannan , Sanjeev Khanna

We give a new deterministic algorithm that non-adaptively learns a hidden hypergraph from edge-detecting queries. All previous non-adaptive algorithms either run in exponential time or have non-optimal query complexity. We give the first…

Machine Learning · Computer Science 2015-02-17 Hasan Abasi , Nader H. Bshouty , Hanna Mazzawi

We describe a new family of $k$-uniform hypergraphs with independent random edges. The hypergraphs have a high probability of being peelable, i.e. to admit no sub-hypergraph of minimum degree $2$, even when the edge density (number of edges…

Data Structures and Algorithms · Computer Science 2019-07-11 Martin Dietzfelbinger , Stefan Walzer

There is a huge difference in techniques and runtimes of distributed algorithms for problems that can be solved by a sequential greedy algorithm and those that cannot. A prime example of this contrast appears in the edge coloring problem:…

Data Structures and Algorithms · Computer Science 2025-05-27 Manuel Jakob , Yannic Maus , Florian Schager

In this paper we consider the problem of reconstructing a hidden weighted hypergraph of constant rank using additive queries. We prove the following: Let $G$ be a weighted hidden hypergraph of constant rank with n vertices and $m$…

Machine Learning · Computer Science 2010-01-05 Nader H. Bshouty , Hanna Mazzawi

We improve the running time of the general algorithmic technique known as Baker's approach (1994) on H-minor-free graphs from O(n^{f(|H|)}) to O(f(|H|) n^{O(1)}). The numerous applications include e.g. a 2-approximation for coloring and…

Data Structures and Algorithms · Computer Science 2015-05-18 Siamak Tazari

We introduce a new ensemble of random bipartite graphs, which we term the `smearing ensemble', where each left node is connected to some number of consecutive right nodes. Such graphs arise naturally in the recovery of sparse wavelet…

Information Theory · Computer Science 2017-05-09 Kabir Chandrasekher , Orhan Ocal , Kannan Ramchandran

This paper aims for set-to-hypergraph prediction, where the goal is to infer the set of relations for a given set of entities. This is a common abstraction for applications in particle physics, biological systems, and combinatorial…

Machine Learning · Computer Science 2023-01-18 David W. Zhang , Gertjan J. Burghouts , Cees G. M. Snoek

Random graph matching refers to recovering the underlying vertex correspondence between two random graphs with correlated edges; a prominent example is when the two random graphs are given by Erd\H{o}s-R\'{e}nyi graphs $G(n,\frac{d}{n})$.…

Machine Learning · Statistics 2020-07-21 Jian Ding , Zongming Ma , Yihong Wu , Jiaming Xu

Given two Erd\H{o}s-R\'enyi graphs with $n$ vertices whose edges are correlated through a latent vertex correspondence, we study complexity lower bounds for the associated correlation detection problem for the class of low-degree polynomial…

Data Structures and Algorithms · Computer Science 2025-11-11 Jian Ding , Hang Du , Zhangsong Li

We study the problem of learning an unknown graph provided via an oracle using a quantum algorithm. We consider three query models. In the first model ("OR queries"), the oracle returns whether a given subset of the vertices contains any…

Quantum Physics · Physics 2021-01-26 Ashley Montanaro , Changpeng Shao

Probabilistic knowledge graph embeddings represent entities as distributions, using learned variances to quantify epistemic uncertainty. We identify a fundamental limitation: these variances are relation-agnostic, meaning an entity receives…

Machine Learning · Computer Science 2026-01-05 Chorok Lee

Despite the recently exhibited importance of higher-order interactions for various processes, few flexible (null) models are available. In particular, most studies on hypergraphs focus on a small set of theoretical models. Here, we…

Statistical Mechanics · Physics 2022-12-28 Marc Barthelemy

Hypergraphs have gained increasing attention in the machine learning community lately due to their superiority over graphs in capturing super-dyadic interactions among entities. In this work, we propose a novel approach for the partitioning…

Machine Learning · Computer Science 2020-11-17 Deepak Maurya , Balaraman Ravindran

Non-uniform hypergraphs appear in various domains of computer science as in the satisfiability problems and in data analysis. We analyse a general model where the probability for an edge of size $t$ to belong to the hypergraph depends of a…

Combinatorics · Mathematics 2015-03-06 Elie de Panafieu

We present a simple nonadaptive randomized algorithm that estimates the number of edges in a simple, unweighted, undirected graph, possibly containing isolated vertices, using only degree and random edge queries. For an $n$-vertex graph,…

Data Structures and Algorithms · Computer Science 2025-12-16 Arijit Bishnu , Debarshi Chanda , Buddha Dev Das , Arijit Ghosh , Gopinath Mishra

In an $r$-uniform hypergraph on $n$ vertices a tight Hamilton cycle consists of $n$ edges such that there exists a cyclic ordering of the vertices where the edges correspond to consecutive segments of $r$ vertices. We provide a first…

Combinatorics · Mathematics 2021-07-01 Peter Allen , Christoph Koch , Olaf Parczyk , Yury Person

Detection of a planted dense subgraph in a random graph is a fundamental statistical and computational problem that has been extensively studied in recent years. We study a hypergraph version of the problem. Let $G^r(n,p)$ denote the…

Data Structures and Algorithms · Computer Science 2023-04-18 Abhishek Dhawan , Cheng Mao , Alexander S. Wein

The problem of efficiently coloring $3$-colorable graphs with few colors has received much attention on both the algorithmic and inapproximability fronts. We consider exponential time approximations, in which given a parameter $r$, we aim…

Data Structures and Algorithms · Computer Science 2024-06-25 Venkatesan Guruswami , Rhea Jain