8 citations · 20 across the 8 of their papers we have counts for
10 papers
Hyperbolic Graph Representation Learning: Embed in One Metric, Optimize with Another
Federico Larroca, Paola Bermolen, Marcelo Fiori +1
Hierarchical graphs embed in hyperbolic space with lower distortion than in Euclidean space owing to its negative curvature. However, their gradient-based learning is hampered at l…
Weighted Random Dot Product Graphs
Bernardo Marenco, Paola Bermolen, Marcelo Fiori +2
Modeling of intricate relational patterns has become a cornerstone of contemporary statistical research and related data science fields. Networks, represented as graphs, offer a na…
Efficiency of Parallel and Restart Exploration Strategies in Model Free Stochastic Simulations
Ernesto Garcia, Paola Bermolen, Matthieu Jonckheere +1
We analyze the efficiency of parallelization and restart mechanisms for stochastic simulations in model-free settings, where the underlying system dynamics are unknown. Such settin…
Gradient-Based Spectral Embeddings of Random Dot Product Graphs
Marcelo Fiori, Bernardo Marenco, Federico Larroca +2
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 po…
Online Change Point Detection for Weighted and Directed Random Dot Product Graphs
Bernardo Marenco, Paola Bermolen, Marcelo Fiori +2
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…
Sequential Algorithms and Independent Sets Discovering on Large Sparse Random Graphs
Paola Bermolen, Matthieu Jonckheere, Federico Larroca +1
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 ran…
Large Deviation Principle for the Greedy Exploration Algorithm over Erdös-Rényi Graphs
P. Bermolen, V. Goicoechea, M. Jonckheere +1
We prove a large deviation principle for a greedy exploration process on an Erdös-Rényi (ER) graph when the number of nodes goes to infinity. To prove our main result, we use the g…
Scaling Limits and Generic Bounds for Exploration Processes
Paola Bermolen, Matthieu Jonckheere, Jaron Sanders
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 ea…
Scaling limits for exploration algorithms
Paola Bermolen, Matthieu Jonckheere, Jaron Sanders
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 growing to in…
Estimating the Spatial Reuse with Configuration Models
Paola Bermolen, Matthieu Jonckheere, Federico Larroca +1
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…