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A $k$-uniform hypergraph $H = (V, E)$ is called $\ell$-orientable, if there is an assignment of each edge $e\in E$ to one of its vertices $v\in e$ such that no vertex is assigned more than $\ell$ edges. Let $H_{n,m,k}$ be a hypergraph,…

Discrete Mathematics · Computer Science 2019-02-20 Nikolaos Fountoulakis , Megha Khosla , Konstantinos Panagiotou

Let $h>w>0$ be two fixed integers. Let $\orH$ be a random hypergraph whose hyperedges are all of cardinality $h$. To {\em $w$-orient} a hyperedge, we assign exactly $w$ of its vertices positive signs with respect to the hyperedge, and the…

Combinatorics · Mathematics 2015-07-29 Pu Gao , Nicholas Wormald

A h-uniform hypergraph H=(V,E) is called (l,k)-orientable if there exists an assignment of each hyperedge e to exactly l of its vertices such that no vertex is assigned more than k hyperedges. Let H_{n,m,h} be a hypergraph, drawn uniformly…

Probability · Mathematics 2012-01-26 Marc Lelarge

For a $k$-uniform hypergraph $F$ let $\textrm{ex}(n,F)$ be the maximum number of edges of a $k$-uniform $n$-vertex hypergraph $H$ which contains no copy of $F$. Determining or estimating $\textrm{ex}(n,F)$ is a classical and central problem…

Combinatorics · Mathematics 2020-12-18 Christian Reiher

We aim to find orientations of mixed graphs optimizing the total reachability, a problem that has applications in causality and biology. For given a digraph $D$, we use $P(D)$ for the set of ordered pairs of distinct vertices in $V(D)$ and…

Computational Complexity · Computer Science 2025-09-24 Florian Hörsch

We determine the probability thresholds for the existence of monotone paths, of finite and infinite length, in random oriented graphs with vertex set $\mathbb N^{[k]}$, the set of all increasing $k$-tuples in $\mathbb N$. These graphs…

Probability · Mathematics 2016-10-05 Pietro Majer , Matteo Novaga

If $G$ is a graph and $\vec H$ is an oriented graph, we write $G\to \vec H$ to say that every orientation of the edges of $G$ contains $\vec H$ as a subdigraph. We consider the case in which $G=G(n,p)$, the binomial random graph. We…

Dietzfelbinger and Weidling [DW07] proposed a natural variation of cuckoo hashing where each of $cn$ objects is assigned $k = 2$ intervals of size $\ell$ in a linear (or cyclic) hash table of size $n$ and both start points are chosen…

Data Structures and Algorithms · Computer Science 2019-12-18 Stefan Walzer

In the Upper Degree-Constrained Partial Orientation problem we are given an undirected graph $G=(V,E)$, together with two degree constraint functions $d^-,d^+ : V \to \mathbb{N}$. The goal is to orient as many edges as possible, in such a…

Data Structures and Algorithms · Computer Science 2014-10-13 Marek Cygan , Tomasz Kociumaka

The paper focuses on two problems: (i) how to orient the edges of an undirected graph in order to maximize the number of ordered vertex pairs (x,y) such that there is a directed path from x to y, and (ii) how to orient the edges so as to…

Data Structures and Algorithms · Computer Science 2015-06-02 S. L. Hakimi , E. Schmeichel , Neal E. Young

A solution to a problem of Erd\H{o}s, Rubin and Taylor is obtained by showing that if a graph $G$ is $(a:b)$-choosable, and $c/d > a/b$, then $G$ is not necessarily $(c:d)$-choosable. The simplest case of another problem, stated by the same…

Discrete Mathematics · Computer Science 2008-02-18 Shai Gutner

Given a hypergraph with uncertain node weights following known probability distributions, we study the problem of querying as few nodes as possible until the identity of a node with minimum weight can be determined for each hyperedge.…

Data Structures and Algorithms · Computer Science 2021-07-02 Evripidis Bampis , Christoph Dürr , Thomas Erlebach , Murilo S. de Lima , Nicole Megow , Jens Schlöter

This article connects the theory of extremal doubly stochastic measures to the geometry and topology of optimal transportation. We begin by reviewing an old question (# 111) of Birkhoff in probability and statistics [4], which is to give a…

Probability · Mathematics 2010-04-26 Najma Ahmad , Hwa Kil Kim , Robert J. McCann

We consider the problem of inferring a matching hidden in a weighted random $k$-hypergraph. We assume that the hyperedges' weights are random and distributed according to two different densities conditioning on the fact that they belong to…

Disordered Systems and Neural Networks · Physics 2022-11-11 Urte Adomaityte , Anshul Toshniwal , Gabriele Sicuro , Lenka Zdeborová

Iterative load balancing algorithms for indivisible tokens have been studied intensively in the past. Complementing previous worst-case analyses, we study an average-case scenario where the load inputs are drawn from a fixed probability…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-03-28 Leran Cai , Thomas Sauerwald

In this paper, we show how one may (efficiently) construct two types of extremal combinatorial objects whose existence was previously conjectural. (*) Panchromatic Graphs: For fixed integer k, a k-panchromatic graph is, roughly speaking, a…

Computational Complexity · Computer Science 2021-11-11 Boris Bukh , Karthik C. S. , Bhargav Narayanan

This paper presents massively parallel computation (MPC) algorithms in the strongly sublinear memory regime (aka, scalable MPC) for orienting and coloring graphs as a function of its subgraph density. Our algorithms run in $poly(\log\log…

Data Structures and Algorithms · Computer Science 2026-03-12 Mohsen Ghaffari , Christoph Grunau

We determine to within a constant factor the threshold for the property that two random k-uniform hypergraphs with edge probability p have an edge-disjoint packing into the same vertex set. More generally, we allow the hypergraphs to have…

Combinatorics · Mathematics 2016-03-01 Béla Bollobás , Svante Janson , Alex Scott

We determine under which conditions certain natural models of random constraint satisfaction problems have sharp thresholds of satisfiability. These models include graph and hypergraph homomorphism, the $(d,k,t)$-model, and binary…

Combinatorics · Mathematics 2009-03-17 Hamed Hatami , Michael Molloy

The maximum likelihood threshold (MLT) of a graph $G$ is the minimum number of samples to almost surely guarantee existence of the maximum likelihood estimate in the corresponding Gaussian graphical model. We give a new characterization of…

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