Zobrazeno 1 - 10
of 68
pro vyhledávání: '"Bermolen, P."'
The Random Dot Product Graph (RDPG) is a generative model for relational data, where nodes are represented via latent vectors in low-dimensional Euclidean space. RDPGs crucially postulate that edge formation probabilities are given by the dot product
Externí odkaz:
http://arxiv.org/abs/2307.13818
Given a sequence of random (directed and weighted) graphs, we address the problem of online monitoring and detection of changes in the underlying data distribution. Our idea is to endow sequential change-point detection (CPD) techniques with a graph
Externí odkaz:
http://arxiv.org/abs/2201.11222
We prove a large deviation principle for the greedy exploration of configuration models, building on a time-discretized version of the method proposed by Bermolen et al. and Brightwell et al. for jointly constructing a random graph from a given degre
Externí odkaz:
http://arxiv.org/abs/2112.12501
Computing the size of maximum independent sets is a NP-hard problem for fixed graphs. Characterizing and designing efficient algorithms to estimate this independence number for random graphs are notoriously difficult and still largely open issues. In
Externí odkaz:
http://arxiv.org/abs/2009.14574
We prove a large deviation principle for a greedy exploration process on an Erd\"os-R\'enyi (ER) graph when the number of nodes goes to infinity. To prove our main result, we use the general strategy to study large deviations of processes proposed by
Externí odkaz:
http://arxiv.org/abs/2007.04753
Autor:
Miriam Gladys Bermolen, Esteban Funosas, María de los Ángeles Giaquinta, Paula Cristina Pedreira, Claudia Rodriguez, Mariana Zanotti
Publikováno v:
Revista de la Asociación Odontológica Argentina, Vol 111, Iss 2 (2023)
Resumen La Sociedad Argentina de Periodoncia ha formulado un Comentario, analizando los condicionantes del contexto nacional, para determinar si las recomendaciones generadas en la Guía de Práctica Clínica de nivel S3 de la Federación Europea de
Externí odkaz:
https://doaj.org/article/2aa5960cb709472eaa8920139fa1154e
We consider exploration algorithms of the random sequential adsorption type both for homogeneous random graphs and random geometric graphs based on spatial Poisson processes. At each step, a vertex of the graph becomes active and its neighboring node
Externí odkaz:
http://arxiv.org/abs/1612.09347
We consider an exploration algorithm where at each step, a random number of items become active while related items get explored. Given an initial number of items $N$ growing to infinity and building on a strong homogeneity assumption, we study using
Externí odkaz:
http://arxiv.org/abs/1504.02438
We propose a new methodology to estimate the spatial reuse of CSMA-like scheduling. Instead of focusing on spatial configurations of users, we model the interferences between users as a random graph. Using configuration models for random graphs, we s
Externí odkaz:
http://arxiv.org/abs/1411.0143
Autor:
Christian Fachola, Agustín Tornaría, Paola Bermolen, Germán Capdehourat, Lorena Etcheverry, María Inés Fariello
Publikováno v:
Data, Vol 8, Iss 2, p 43 (2023)
Federated learning techniques aim to train and build machine learning models based on distributed datasets across multiple devices while avoiding data leakage. The main idea is to perform training on remote devices or isolated data centers without tr
Externí odkaz:
https://doaj.org/article/e05ba71fa65f4533981adbf3844563f9