activity
20152025
most citedAdaptive Diffusion Schemes for Heterogeneous Networks

40 citations · 98 across the 6 of their papers we have counts for

collaborators

6 papers

cs.MA2025★ 1 cited

Asymptotic analysis of cooperative censoring policies in sensor networks

Jesus Fernandez-Bes, Rocío Arroyo-Valles, Jesús Cid-Sueiro

The problem of cooperative data censoring in battery-powered multihop sensor networks is analyzed in this paper. We are interested in scenarios where nodes generate messages (which…

eess.SY2025★ 20 cited

An MDP Model for Censoring in Harvesting Sensors: Optimal and Approximated Solutions

Jesus Fernandez-Bes, Jesus Cid-Sueiro, Antonio G. Marques

In this paper, we propose a novel censoring policy for energy-efficient transmissions in energy-harvesting sensors. The problem is formulated as an infinite-horizon Markov Decision…

stat.ML2016

On the Relationship between Online Gaussian Process Regression and Kernel Least Mean Squares Algorithms

Steven Van Vaerenbergh, Jesus Fernandez-Bes, Víctor Elvira

We study the relationship between online Gaussian process (GP) regression and kernel least mean squares (KLMS) algorithms. While the latter have no capacity of storing the entire p…

eess.SY2015★ 4 cited

Censoring Diffusion for Harvesting WSNs

Jesus Fernandez-Bes, Rocío Arroyo-Valles, Jerónimo Arenas-García +1

In this paper, we analyze energy-harvesting adaptive diffusion networks for a distributed estimation problem. In order to wisely manage the available energy resources, we propose a…

eess.SY2015★ 40 cited

Adaptive Diffusion Schemes for Heterogeneous Networks

Jesus Fernandez-Bes, Jerónimo Arenas-García, Magno T. M. Silva +1

In this paper, we deal with distributed estimation problems in diffusion networks with heterogeneous nodes, i.e., nodes that either implement different adaptive rules or differ in…

stat.ML2015★ 33 cited

A Probabilistic Least-Mean-Squares Filter

Jesus Fernandez-Bes, Víctor Elvira, Steven Van Vaerenbergh

We introduce a probabilistic approach to the LMS filter. By means of an efficient approximation, this approach provides an adaptable step-size LMS algorithm together with a measure…