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Consider a density $f$ on $[0,1]$ that must be estimated from an i.i.d. sample $X_1,...,X_n$ drawn from $f$. In this note, we study binary-tree-based histogram estimates that use recursive splitting of intervals. If the decision to split an…

Statistics Theory · Mathematics 2025-04-24 Luc Devroye , Jad Hamdan

Learning a regression function using censored or interval-valued output data is an important problem in fields such as genomics and medicine. The goal is to learn a real-valued prediction function, and the training output labels indicate an…

Machine Learning · Statistics 2017-10-30 Alexandre Drouin , Toby Dylan Hocking , François Laviolette

This work presents novel algorithms for learning Bayesian network structures with bounded treewidth. Both exact and approximate methods are developed. The exact method combines mixed-integer linear programming formulations for structure…

Artificial Intelligence · Computer Science 2014-06-09 Siqi Nie , Denis Deratani Maua , Cassio Polpo de Campos , Qiang Ji

We shift the perspective on the interval fragmentation problem from division points to division spacings. This leads to a proof that is both simpler and stronger, establishing limiting distributions for partition points and spacings and,…

Probability · Mathematics 2025-08-26 Changqing Liu

The phase transition in the number partitioning problem (NPP), i.e., the transition from a region in the space of control parameters in which almost all instances have many solutions to a region in which almost all instances have no…

Condensed Matter · Physics 2016-08-16 Peter F. Stadler , Wim Hordijk , José F. Fontanari

We develop a finite-sample, design-based theory for random forests in which each tree is a randomized conditional predictor acting on fixed covariates and the forest is their Monte Carlo average. An exact variance identity separates Monte…

Machine Learning · Statistics 2026-03-03 Nathaniel S. O'Connell

We revisit binary decision trees from the perspective of partitions of the data. We introduce the notion of partitioning function, and we relate it to the growth function and to the VC dimension. We consider three types of features:…

Machine Learning · Statistics 2022-10-21 Jean-Samuel Leboeuf , Frédéric LeBlanc , Mario Marchand

Consider the d-dimensional lattice Z^d where each vertex is ``open'' or ``closed'' with probability p or 1-p, respectively. An open vertex v is connected by an edge to the closest open vertex w such that the dth co-ordinates of v and w…

Probability · Mathematics 2016-09-07 Sreela Gangopadhyay , Rahul Roy , Anish Sarkar

The exactly solvable four-vertex model with the fixed boundary conditions in the presence of inhomogeneous linearly growing external field is considered. The partition function of the model is calculated and represented in the determinantal…

Statistical Mechanics · Physics 2020-11-23 Nikolay Bogoliubov , Cyril Malyshev

Two kinds of approximation algorithms exist for the k-BALANCED PARTITIONING problem: those that are fast but compute unsatisfying approximation ratios, and those that guarantee high quality ratios but are slow. In this paper we prove that…

Computational Complexity · Computer Science 2019-04-29 Andreas Emil Feldmann

The recursive and hierarchical structure of full rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. In most of these cases, the full rooted tree is…

Machine Learning · Statistics 2022-03-24 Yuta Nakahara , Shota Saito , Akira Kamatsuka , Toshiyasu Matsushima

Consider an infinite tree with random degrees, i.i.d. over the sites, with a prescribed probability distribution with generating function G(s). We consider the following variation of Renyi's parking problem, alternatively called blocking…

Probability · Mathematics 2009-11-13 H. Dehling , S. R. Fleurke , C. Kuelske

We derive the exact generating function for planar maps (genus zero fatgraphs) with vertices of arbitrary even valence and with two marked points at a fixed geodesic distance. This is done in a purely combinatorial way based on a bijection…

Statistical Mechanics · Physics 2010-04-05 J. Bouttier , P. Di Francesco , E. Guitter

Optimal transport (\OT) theory defines a powerful set of tools to compare probability distributions. \OT~suffers however from a few drawbacks, computational and statistical, which have encouraged the proposal of several regularized variants…

Machine Learning · Statistics 2019-10-29 Tam Le , Makoto Yamada , Kenji Fukumizu , Marco Cuturi

We study random unrooted plane trees with $n$ vertices sampled according to the weights corresponding to the vertex-degrees. Our main result shows that if the generating series of the weights has positive radius of convergence, then this…

Probability · Mathematics 2018-09-17 Leon Ramzews , Benedikt Stufler

We study the large-deviation properties of minimum spanning trees for two ensembles of random graphs with $N$ nodes. First, we consider complete graphs. Second, we study Erd\H{o}s-R\'{e}nyi (ER) random graphs with edge probability $p=c/N$…

Disordered Systems and Neural Networks · Physics 2025-12-16 Mahdi Sarikhani , Alexander K. Hartmann

In the planted partition problem, the $n$ vertices of a random graph are partitioned into $k$ "clusters," and edges between vertices in the same cluster and different clusters are included with constant probability $p$ and $q$, respectively…

Data Structures and Algorithms · Computer Science 2017-08-24 Sam Cole

We study fragmentation of a random recursive tree into a forest by repeated removal of nodes. The initial tree consists of N nodes and it is generated by sequential addition of nodes with each new node attaching to a randomly-selected…

Statistical Mechanics · Physics 2014-12-25 Z. Kalay , E. Ben-Naim

In this work, we study the color discrepancy of spanning trees in random graphs. We show that for the Erd\H{o}s-R\'enyi random graph $G(n,p)$ with $p$ above the connectivity threshold, the following holds with high probability: in every…

Combinatorics · Mathematics 2025-11-10 Wenchong Chen , Xiao-Chuan Liu , Xu Yang

We study the problem of estimating the density $f(\boldsymbol x)$ of a random vector ${\boldsymbol X}$ in $\mathbb R^d$. For a spanning tree $T$ defined on the vertex set $\{1,\dots ,d\}$, the tree density $f_{T}$ is a product of bivariate…

Statistics Theory · Mathematics 2022-09-23 László Györfi , Aryeh Kontorovich , Roi Weiss