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In this work, we are interested in the set of visited vertices of a tree $\mathbb{T}$ by a randomly biased random walk $\mathbb{X}:=(X_n,n \in \mathbb{N})$. The aim is to study a generalized range, that is to say the volume of the trace of…

Probability · Mathematics 2024-09-20 Pierre Andreoletti , Alexis Kagan

Regularized regression has become very popular nowadays, particularly on high-dimensional problems where the addition of a penalty term to the log-likelihood allows inference where traditional methods fail. A number of penalties have been…

Methodology · Statistics 2021-02-15 Hamed Haselimashhadi , Veronica Vinciotti

We consider point clouds obtained as random samples of a measure on a Euclidean domain. A graph representing the point cloud is obtained by assigning weights to edges based on the distance between the points they connect. Our goal is to…

Statistics Theory · Mathematics 2015-10-28 Nicolás García Trillos , Dejan Slepčev

We show that for any fixed dense graph G and bounded-degree tree T on the same number of vertices, a modest random perturbation of G will typically contain a copy of T . This combines the viewpoints of the well-studied problems of embedding…

Combinatorics · Mathematics 2025-05-30 Michael Krivelevich , Matthew Kwan , Benny Sudakov

We introduce the concept of Most, and Least, Compact Spanning Trees - denoted respectively by $T^*(G)$ and $T^\#(G)$ - of a simple, connected, undirected and unweighted graph $G(V, E, W)$. For a spanning tree $T(G) \in \mathcal{T}(G)$ to be…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-22 Gyan Ranjan , Nishant Saurabh , Amit Ashutosh

Parameterised subgraph counting problems are the most thoroughly studied topic in the theory of parameterised counting, and there has been significant recent progress in this area. Many of the existing tractability results for parameterised…

Computational Complexity · Computer Science 2015-06-01 Kitty Meeks

Sparse parametric models are of great interest in statistical learning and are often analyzed by means of regularized estimators. Pathwise methods allow to efficiently compute the full solution path for penalized estimators, for any…

Machine Learning · Statistics 2024-12-06 Alessandro De Gregorio , Francesco Iafrate

Probabilistic graphical models offer a powerful framework to account for the dependence structure between variables, which is represented as a graph. However, the dependence between variables may render inference tasks intractable. In this…

Graph alignment - identifying node correspondences between two graphs - is a fundamental problem with applications in network analysis, biology, and privacy research. While substantial progress has been made in aligning correlated…

Information Theory · Computer Science 2026-03-16 Jakob Maier , Laurent Massoulié

Motivated by a conjecture of Gy\'arf\'as, recently B\"ottcher, Hladk\'y, Piguet, and Taraz showed that every collection $T_1,\dots,T_t$ of trees on $n$ vertices with $\sum_{i=1}^te(T_i)\leq \binom{n}{2}$ and with bounded maximum degree, can…

Combinatorics · Mathematics 2016-04-20 Silvia Messuti , Vojtěch Rödl , Mathias Schacht

With applications in distribution systems and communication networks, the minimum stretch spanning tree problem is to find a spanning tree T of a graph G such that the maximum distance in T between two adjacent vertices is minimized. The…

Combinatorics · Mathematics 2017-12-12 Lan Lin , Yixun Lin

We focus on counting the number of labeled graphs on $n$ vertices and treewidth at most $k$ (or equivalently, the number of labeled partial $k$-trees), which we denote by $T_{n,k}$. So far, only the particular cases $T_{n,1}$ and $T_{n,2}$…

Combinatorics · Mathematics 2016-04-26 Julien Baste , Marc Noy , Ignasi Sau

This paper considers the penalized least squares estimator with arbitrary convex penalty. When the observation noise is Gaussian, we show that the prediction error is a subgaussian random variable concentrated around its median. We apply…

Statistics Theory · Mathematics 2016-09-22 Pierre C. Bellec , Alexandre B. Tsybakov

We address several related problems on combinatorial discrepancy of trees in a setting introduced by Erd\H{o}s, F\"{u}redi, Loebl and S\'{o}s. Given a fixed tree $T$ on $n$ vertices and an edge-colouring of the complete graph $K_n$, for…

Combinatorics · Mathematics 2024-10-23 Lawrence Hollom , Lyuben Lichev , Adva Mond , Julien Portier

We consider the following graph reconstruction problem: given an unweighted connected graph $G = (V,E)$ with visible vertex set $V$ and an oracle which takes two vertices $u,v \in V$ and returns the shortest path distance between $u$ and…

Data Structures and Algorithms · Computer Science 2026-03-12 Chirag Kaudan , Amir Nayyeri

The problems of model and variable selections for classification trees are jointly considered. A penalized criterion is proposed which explicitly takes into account the number of variables, and a risk bound inequality is provided for the…

Statistics Theory · Mathematics 2012-06-27 Servane Gey , Tristan Mary-Huard

We give formulas, in terms of graph theoretical invariants, for the minimum distance and the generalized Hamming weights of the linear code generated by the rows of the incidence matrix of a signed graph over a finite field, and for those…

Information Theory · Computer Science 2020-09-10 Jose Martinez-Bernal , Miguel A. Valencia , Rafael H. Villarreal

We study reachability and shortest paths problems in dynamic directed graphs. Whereas algebraic dynamic data structures supporting edge updates and reachability/distance queries have been known for quite a long time, they do not, in…

Data Structures and Algorithms · Computer Science 2022-04-01 Adam Karczmarz , Anish Mukherjee , Piotr Sankowski

Many discrete optimization problems amount to selecting a feasible set of edges of least weight. We consider in this paper the context of spatial graphs where the positions of the vertices are uncertain and belong to known uncertainty sets.…

Data Structures and Algorithms · Computer Science 2022-09-27 Marin Bougeret , Jérémy Omer , Michael Poss

Despite widespread interest and practical use, the theoretical properties of random forests are still not well understood. In this paper we contribute to this understanding in two ways. We present a new theoretically tractable variant of…

Machine Learning · Statistics 2013-10-08 Misha Denil , David Matheson , Nando de Freitas
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