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Rooted, weighted continuum random trees are used to describe limits of sequences of random discrete trees. Formally, they are random quadruples $(\mathcal{T},d,r,p)$, where $(\mathcal{T},d)$ is a tree-like metric space, $r\in\mathcal{T}$ is…

Probability · Mathematics 2021-01-29 Noah Forman

Rooted binary perfect phylogenies provide a generalization of rooted binary unlabeled trees in which each leaf is assigned a positive integer value that corresponds in a biological setting to the count of the number of indistinguishable…

Populations and Evolution · Quantitative Biology 2024-10-22 Chloe E. Shiff , Noah A. Rosenberg

Given a set S of n \geq d points in general position in R^d, a random hyperplane split is obtained by sampling d points uniformly at random without replacement from S and splitting based on their affine hull. A random hyperplane search tree…

Computational Geometry · Computer Science 2011-06-03 Luc Devroye , James King

A finite graph embedded in the plane is called a series-parallel map if it can be obtained from a finite tree by repeatedly subdividing and doubling edges. We study the scaling limit of weighted random two-connected series-parallel maps…

Controversy exists on whether differentiable neural architecture search methods discover wiring topology effectively. To understand how wiring topology evolves, we study the underlying mechanism of several existing differentiable NAS…

Machine Learning · Computer Science 2021-02-26 Sirui Xie , Shoukang Hu , Xinjiang Wang , Chunxiao Liu , Jianping Shi , Xunying Liu , Dahua Lin

A communication network can be modeled as a directed connected graph with edge weights that characterize performance metrics such as loss and delay. Network tomography aims to infer these edge weights from their pathwise versions measured…

Optimization and Control · Mathematics 2019-08-12 Mahmood Ettehad , Nick Duffield , Gregory Berkolaiko

We consider directed weighted graphs and define various families of path counting functions. Our main results are explicit formulas for the main term of the asymptotic growth rate of these counting functions, under some irrationality…

Combinatorics · Mathematics 2019-09-26 Avner Kiro , Yotam Smilansky , Uzy Smilansky

Discriminative Random Walks (DRWs) are a simple yet powerful tool for semi-supervised node classification, but their theoretical foundations remain fragmentary. We revisit DRWs through the lens of information geometry, treating the family…

Machine Learning · Statistics 2026-02-10 Masanari Kimura

We establish limit theorems that describe the asymptotic local and global geometric behaviour of random enriched trees considered up to symmetry. We apply these general results to random unlabelled weighted rooted graphs and uniform random…

Probability · Mathematics 2016-12-15 Benedikt Stufler

Many of the distributed localization algorithms are based on relaxed optimization formulations of the localization problem. These algorithms commonly rely on first-order optimization methods, and hence may require many iterations or…

Optimization and Control · Mathematics 2016-07-19 Sina Khoshfetrat Pakazad , Emre Özkan , Carsten Fritsche , Anders Hansson , Fredrik Gustafsson

In this paper, we study the impact of edge weights on distances in diluted random graphs. We interpret these weights as delays, and take them as i.i.d exponential random variables. We analyze the weighted flooding time defined as the…

Probability · Mathematics 2010-11-30 Hamed Amini , Moez Draief , Marc Lelarge

We present a randomized algorithm for reconstructing directed rooted trees of $n$ nodes and node degree at most $d$, by asking at most $O(dn\log^2 n)$ path queries. Each path query takes as input an origin node and a target node, and…

Data Structures and Algorithms · Computer Science 2017-11-20 Zhaosen Wang , Jean Honorio

We show that prominent centrality measures in network analysis are all based on additively separable and linear treatments of statistics that capture a node's position in the network. This enables us to provide a taxonomy of centrality…

Physics and Society · Physics 2021-01-25 Francis Bloch , Matthew O. Jackson , Pietro Tebaldi

Representing nodes in a network as dense vectors node embeddings is important for understanding a given network and solving many downstream tasks. In particular, for weighted homophilous graphs where similar nodes are connected with larger…

Social and Information Networks · Computer Science 2023-08-14 Jun Hee Kim , Jaeman Son , Hyunsoo Kim , Eunjo Lee

We define a class of properties on random plane trees, which we call subtree additive properties, inspired by the combinatorics of certain biologically-interesting properties in a plane tree model of RNA secondary structure. The class of…

Combinatorics · Mathematics 2021-01-15 Anna Kirkpatrick , Chidozie Onyeze

We introduce and study the general setting of weighted search in which a number of targets, each with a certain weight, are hidden in a star-like environment that consists of $m$ infinite, concurrent rays, with a common origin. A mobile…

Data Structures and Algorithms · Computer Science 2021-05-05 Spyros Angelopoulos , Konstantinos Panagiotou

Real-data networks often appear to have strong modularity, or network-of-networks structure, in which subgraphs of various size and consistency occur. Finding the respective subgraph structure is of great importance, in particular for…

Physics and Society · Physics 2008-09-29 Mitrovic Marija , Bosiljka Tadic

When dealing with large graphs, such as those that arise in the context of online social networks, a subset of nodes may be labeled. These labels can indicate demographic values, interest, beliefs or other characteristics of the nodes…

Social and Information Networks · Computer Science 2015-05-27 Smriti Bhagat , Graham Cormode , S. Muthukrishnan

Grouping the nodes of a graph into clusters is a standard technique for studying networks. We study a problem where we are given a directed network and are asked to partition the graph into a sequence of coherent groups. We assume that…

Social and Information Networks · Computer Science 2025-12-08 Iiro Kumpulainen , Nikolaj Tatti

The treedepth of a graph $G$ is the least possible depth of an elimination forest of $G$: a rooted forest on the same vertex set where every pair of vertices adjacent in $G$ is bound by the ancestor/descendant relation. We propose an…

Data Structures and Algorithms · Computer Science 2022-05-06 Wojciech Nadara , Michał Pilipczuk , Marcin Smulewicz