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When solving ill-posed inverse problems, one often desires to explore the space of potential solutions rather than be presented with a single plausible reconstruction. Valuable insights into these feasible solutions and their associated…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Elias Nehme , Rotem Mulayoff , Tomer Michaeli

We consider a discrete-time dynamical process on graphs, firstly introduced in connection with a protocol for controlling large networks of spin 1/2 quantum mechanical particles [Phys. Rev. Lett. 99, 100501 (2007)]. A description is as…

Combinatorics · Mathematics 2013-09-17 Simone Severini

Several real-world and abstract structures and systems are characterized by marked hierarchy to the point of being expressed as trees. Because the study of these entities often involves sampling (or discovering) the tree nodes in a specific…

Physics and Society · Physics 2022-04-18 Alexandre Benatti , Luciano da F. Costa

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

In the Telephone Broadcast problem we are given a graph $G=(V,E)$ with a designated source vertex $s\in V$. Our goal is to transmit a message, which is initially known only to $s$, to all vertices of the graph by using a process where in…

Data Structures and Algorithms · Computer Science 2025-04-21 Yudai Egami , Tatsuya Gima , Tesshu Hanaka , Yasuaki Kobayashi , Michael Lampis , Valia Mitsou , Edouard Nemery , Yota Otachi , Manolis Vasilakis , Daniel Vaz

Random forests construct each tree with a different, randomised representation of the feature space. Their uniform voting cannot correct errors in regions where trees with incorrect representations probabilistically outnumber correct ones,…

Machine Learning · Computer Science 2026-05-28 Youngjoon Park

The information reconstruction problem on an infinite tree, is to collect and analyze massive data samples at the $n$th level of the tree to identify whether there is non-vanishing information of the root, as $n$ goes to infinity. This…

Probability · Mathematics 2019-10-02 Wenjian Liu , Ning Ning

We study a specialization of the problem of broadcasting on directed acyclic graphs, namely, broadcasting on 2D regular grids. Consider a 2D regular grid with source vertex $X$ at layer $0$ and $k+1$ vertices at layer $k\geq 1$, which are…

Probability · Mathematics 2022-09-20 Anuran Makur , Elchanan Mossel , Yury Polyanskiy

Neural Networks and Decision Trees: two popular techniques for supervised learning that are seemingly disconnected in their formulation and optimization method, have recently been combined in a single construct. The connection pivots on…

Machine Learning · Statistics 2020-02-27 Giuseppe Nuti , Lluís Antoni Jiménez Rugama , Kaspar Thommen

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

The analysis of Belief Propagation and other algorithms for the {\em reconstruction problem} plays a key role in the analysis of community detection in inference on graphs, phylogenetic reconstruction in bioinformatics, and the cavity…

Information Theory · Computer Science 2019-05-27 Vishesh Jain , Frederic Koehler , Jingbo Liu , Elchanan Mossel

The problem of sending two correlated vector Gaussian sources over a bandwidth-matched two-user scalar Gaussian broadcast channel is studied in this work, where each receiver wishes to reconstruct its target source under a covariance…

Information Theory · Computer Science 2015-03-11 Lin Song , Jun Chen , Chao Tian

We consider parameter estimation in distributed networks, where each sensor in the network observes an independent sample from an underlying distribution and has $k$ bits to communicate its sample to a centralized processor which computes…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-07-23 Yanjun Han , Ayfer Özgür , Tsachy Weissman

This paper explores the distributed broadcast problem within the context of network communications, a critical challenge in decentralized information dissemination. We put forth a novel hypergraph-based approach to address this issue,…

Information Theory · Computer Science 2025-09-09 Qi Cao , Yulin Shao , Fan Yang , Octavia A. Dobre

We consider a branching random walk with binary state space and index set $T^k$, the infinite rooted tree in which each node has k children (also known as the model of "broadcasting on a tree"). The root of the tree takes a random value 0…

Probability · Mathematics 2007-05-23 James B. Martin

Cut-set bounds on achievable rates for network communication protocols are not in general tight. In this paper we introduce a new technique for proving converses for the problem of transmission of correlated sources in networks, that…

Information Theory · Computer Science 2011-05-31 Amin Aminzadeh Gohari , Shenghao Yang , Sidharth Jaggi

In the critical beta-splitting model of a random $n$-leaf binary tree, leaf-sets are recursively split into subsets, and a set of $m$ leaves is split into subsets containing $i$ and $m-i$ leaves with probabilities proportional to…

Probability · Mathematics 2024-09-09 David Aldous , Boris Pittel

We give a time-randomness tradeoff for the quasi-random rumor spreading protocol proposed by Doerr, Friedrich and Sauerwald [SODA 2008] on complete graphs. In this protocol, the goal is to spread a piece of information originating from one…

Data Structures and Algorithms · Computer Science 2010-08-04 Benjamin Doerr , Mahmoud Fouz

A weighted recursive tree is an evolving tree in which vertices are assigned random vertex-weights and new vertices connect to a predecessor with a probability proportional to its weight. Here, we study the maximum degree and near-maximum…

Probability · Mathematics 2023-01-31 Laura Eslava , Bas Lodewijks , Marcel Ortgiese

We derive a renormalization method to calculate the spectral dimension $\bar{d}$ of deterministic self-similar networks with arbitrary base units and branching constants. The generality of the method allows the affect of a multitude of…

Statistical Mechanics · Physics 2015-05-13 Christophe P. Haynes , Anthony P. Roberts