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Label distribution learning (LDL) is a general learning framework, which assigns to an instance a distribution over a set of labels rather than a single label or multiple labels. Current LDL methods have either restricted assumptions on the…

Machine Learning · Computer Science 2017-10-18 Wei Shen , Kai Zhao , Yilu Guo , Alan Yuille

We study the problem of approximating a discrete probability distribution, such as the next-token distribution of a large language model, by a dyadic distribution induced by a binary tree under encoding rate constraints. The objective is to…

Information Theory · Computer Science 2026-05-08 Daniella Bar-Lev , Farzad Farnoud , Ryan Gabrys

We study the statistical properties of large random networks with specified degree distributions. New techniques are presented for analyzing the structure of social networks. Specifically, we address the question of how many nodes exist at…

Physics and Society · Physics 2007-05-23 Erik Volz

We prove that if a tree $T$ has $n$ vertices and maximum degree at most $\Delta$, then a copy of $T$ can almost surely be found in the random graph $\mathcal{G}(n,\Delta\log^5 n/n)$.

Combinatorics · Mathematics 2014-06-27 Richard Montgomery

In this paper we introduce a new notion of convergence of sparse graphs which we call Large Deviations or LD-convergence and which is based on the theory of large deviations. The notion is introduced by "decorating" the nodes of the graph…

Probability · Mathematics 2013-02-20 Christian Borgs , Jennifer Chayes , David Gamarnik

Random graphs with a given degree sequence are often constructed using the configuration model, which yields a random multigraph. We may adjust this multigraph by a sequence of switchings, eventually yielding a simple graph. We show that,…

Probability · Mathematics 2019-02-01 Svante Janson

The metric dimension of a graph $G$ is the minimal size of a subset $R$ of vertices of $G$ that, upon reporting their graph distance from a distingished (source) vertex $v^\star$, enable unique identification of the source vertex $v^\star$…

Probability · Mathematics 2021-11-16 Júlia Komjáthy , Gergely Ódor

We prove a large deviation principle for the largest singular value of sparse non-Hermitian random matrices, or directed Erd\H{o}s-R\'enyi networks in the constant average degree regime $p =\frac{d}{n}$ where $d$ is fixed. Entries are…

Probability · Mathematics 2024-06-18 Hyungwon Han

For a tree $T$, let $lp(T)$ be the number of different lengths of leaf to leaf paths in $T$. For a degree sequence $s$ of a tree, let ${\rm rad}(s)$ be the minimum radius of a tree with degree sequence $s$. Recently, Di Braccio,…

Combinatorics · Mathematics 2025-07-25 Dieter Rautenbach , Johannes Scherer , Florian Werner

The goal of this paper is to go further in the analysis of the behavior of the number of descents in a random permutation. Via two different approaches relying on a suitable martingale decomposition or on the Irwin-Hall distribution, we…

Probability · Mathematics 2024-11-20 Bernard Bercu , Michel Bonnefont , Adrien Richou

We establish the rate of convergence in the strong law of large numbers of discrete Fourier Transform of the identically distributed random variables with finite moment of order p, where 1<p<2.

Probability · Mathematics 2016-02-24 Na Zhang

We investigate large deviations for a family of conservative stochastic PDEs (conservation laws) in the asymptotic of jointly vanishing noise and viscosity. We obtain a first large deviations principle in a space of Young measures. The…

Probability · Mathematics 2009-04-06 Mauro Mariani

We study a model of growing planar tree graphs where in each time step we separate the tree into two components by splitting a vertex and then connect the two pieces by inserting a new link between the daughter vertices. This model…

Statistical Mechanics · Physics 2009-11-13 Francois David , Mark Dukes , Thordur Jonsson , Sigurdur Orn Stefansson

We study a random fragmentation process and its associated random tree. The process has earlier been studied by Dean and Majumdar (J. Phys. A: Math. Gen., vol. 35, L501--L507), who found a phase transition: the number of fragmentations is…

Probability · Mathematics 2007-05-23 S. Janson , R. Neininger

We study the properties of random walks on complex trees. We observe that the absence of loops reflects in physical observables showing large differences with respect to their looped counterparts. First, both the vertex discovery rate and…

Statistical Mechanics · Physics 2008-10-21 Andrea Baronchelli , Michele Catanzaro , Romualdo Pastor-Satorras

We comment on old and new results related to the destruction of a random recursive tree (RRT), in which its edges are cut one after the other in a uniform random order. In particular, we study the number of steps needed to isolate or…

Probability · Mathematics 2016-12-28 Erich Baur , Jean Bertoin

Let (X_n,Y_n) be i.i.d. random vectors. Let W(x) be the partial sum of Y_n just before that of X_n exceeds x>0. Motivated by stochastic models for neural activity, uniform convergence of the form $\sup_{c\in I}|a(c,x)\operatorname…

Probability · Mathematics 2009-09-29 Zhiyi Chi

We consider a random tree and introduce a metric in the space of trees to define the ``mean tree'' as the tree minimizing the average distance to the random tree. When the resulting metric space is compact we have laws of large numbers and…

Probability · Mathematics 2007-05-23 David Balding , Pablo A. Ferrari , Ricardo Fraiman , Mariela Sued

We deal with a random graph model where at each step, a vertex is chosen uniformly at random, and it is either duplicated or its edges are deleted. Duplication has a given probability. We analyse the limit distribution of the degree of a…

Probability · Mathematics 2014-09-19 Ágnes Backhausz , Tamás F. Móri

Given $n$ samples of a regular discrete distribution $\pi$, we prove in this article first a serial of SLLNs results (of Dvoretzky and Erd\"{o}s' type) which implies a typical power law when $\pi$ is heavy-tailed. Constructing a (random)…

Probability · Mathematics 2013-12-12 Xin-Xing Chen , Jian-Sheng Xie , Jiangang Ying