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We offer theoretical and empirical insights into the impact of exogenous randomness on the effectiveness of random forests with tree-building rules independent of training data. We formally introduce the concept of exogenous randomness and…

Machine Learning · Statistics 2024-11-13 Tianxing Mei , Yingying Fan , Jinchi Lv

We consider the transmission of a state from the root of a tree towards its leaves, assuming that each transmission occurs through a noisy channel. The states at the leaves are observed, while at deeper nodes we can compute the likelihood…

Information Theory · Computer Science 2022-04-25 Cassius Manuel

Tree-based ensemble methods, as Random Forests and Gradient Boosted Trees, have been successfully used for regression in many applications and research studies. Furthermore, these methods have been extended in order to deal with uncertainty…

Machine Learning · Computer Science 2018-11-20 Myriam Tami , Marianne Clausel , Emilie Devijver , Adrien Dulac , Eric Gaussier , Stefan Janaqi , Meriam Chebre

We study the size and the lifetime distributions of scale-free random branching tree in which $k$ branches are generated from a node at each time step with probability $q_k\sim k^{-\gamma}$. In particular, we focus on finite-size trees in a…

Statistical Mechanics · Physics 2009-11-13 D. -S. Lee , J. S. Kim , B. Kahng , D. Kim

Germ order is a non-standard stochastic order defined through the comparison of the generating functions of the processes. This order was first introduced for branching random walks with a constant breeding law and independent dispersal of…

Probability · Mathematics 2025-08-07 Daniela Bertacchi , Fabio Zucca

When ignorance due to the lack of knowledge, modeled as epistemic uncertainty using Dempster-Shafer structures on closed intervals, is present in the model parameters, a new uncertainty propagation method is necessary to propagate both…

Methodology · Statistics 2011-07-11 Gabriel Terejanu , Puneet Singla , Tarunraj Singh , Peter D. Scott

In this article we discuss estimation of the common variance of several normal populations with tree order restricted means. We discuss the asymptotic properties of the maximum likelihood estimator of the variance as the number of…

Statistics Theory · Mathematics 2014-07-24 Antar Bandyopadhyay , Sanjay Chaudhuri

This paper is concerned with the reliable inference of optimal tree-approximations to the dependency structure of an unknown distribution generating data. The traditional approach to the problem measures the dependency strength between…

Machine Learning · Computer Science 2007-07-16 Marco Zaffalon , Marcus Hutter

We study branching processes in an i.i.d. random environment, where the associated random walk is of the oscillating type. This class of processes generalizes the classical notion of criticality. The main properties of such branching…

Probability · Mathematics 2007-05-23 V. I. Afanasyev , J. Geiger , G. Kersting , V. A. Vatutin

We introduce a new random graph model motivated by biological questions relating to speciation. This random graph is defined as the stationary distribution of a Markov chain on the space of graphs on $\{1, \ldots, n\}$. The dynamics of this…

Probability · Mathematics 2019-06-24 François Bienvenu , Florence Débarre , Amaury Lambert

We study various classes of random processes defined on the regular tree $T_d$ that are invariant under the automorphism group of $T_d$. Most important ones are factor of i.i.d. processes (randomized local algorithms), branching Markov…

Probability · Mathematics 2015-07-28 Ágnes Backhausz , Balázs Szegedy

For the study of information propagation, one fundamental problem is uncovering universal laws governing the dynamics of information propagation. This problem, from the microscopic perspective, is formulated as estimating the propagation…

Social and Information Networks · Computer Science 2014-06-19 Junming Huang , Chao Li , Wen-Qiang Wang , Hua-Wei Shen , Guojie Li , Xue-Qi Cheng

We make the first steps towards generalizing the theory of stochastic block models, in the sparse regime, towards a model where the discrete community structure is replaced by an underlying geometry. We consider a geometric random graph…

Machine Learning · Statistics 2022-07-04 Ronen Eldan , Dan Mikulincer , Hester Pieters

Community structure is an important factor in the behavior of real-world networks because it strongly affects the stability and thus the phase transition order of the spreading dynamics. We here propose a reversible social contagion model…

Physics and Society · Physics 2018-06-13 Zhen Su , Wei Wang , Lixiang Li , H. Eugene Stanley , Lidia A. Braunstein

We study the diffusion of influence in random multiplex networks where links can be of $r$ different types, and for a given content (e.g., rumor, product, political view), each link type is associated with a content dependent parameter…

Physics and Society · Physics 2012-09-11 Osman Yagan , Virgil Gligor

Opinion diffusion is a crucial phenomenon in social networks, often underlying the way in which a collective of agents develops a consensus on relevant decisions. The voter model is a well-known theoretical model to study opinion spreading…

Multiagent Systems · Computer Science 2024-03-14 Luca Becchetti , Vincenzo Bonifaci , Emilio Cruciani , Francesco Pasquale

In this paper, we study random gossip processes in communication models that describe the peer-to-peer networking functionality included in standard smartphone operating systems. Random gossip processes spread information through the basic…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-08 Calvin Newport , Alex Weaver

We propose a stochastic model for the diffusion of topics entering a social network modeled by a Watts-Strogatz graph. Our model sets into play an implicit competition between these topics as they vie for the attention of users in the…

Social and Information Networks · Computer Science 2012-02-13 S. Rajyalakshmi , Amitabha Bagchi , Soham Das , Rudra M. Tripathy

In a deterministic or random tree, a notion of ancestral diversity can be defined as follows. Sample independently $n$ groups of $k$ leaves and count the number $N_n(k)$ of distinct most recent common ancestors of each of the groups. As $n$…

Probability · Mathematics 2025-12-18 Bénédicte Haas , Grégory Miermont

Markovian evolving graphs are dynamic-graph models where the links among a fixed set of nodes change during time according to an arbitrary Markovian rule. They are extremely general and they can well describe important dynamic-network…

Discrete Mathematics · Computer Science 2011-03-04 Andrea Clementi , Angelo Monti , Francesco Pasquale , Riccardo Silvestri
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