Search Results for author: Jerónimo Arenas-García

Found 9 papers, 1 papers with code

Federated Neural Topic Models

1 code implementation5 Dec 2022 Lorena Calvo-Bartolomé, Jerónimo Arenas-García

Over the last years, topic modeling has emerged as a powerful technique for organizing and summarizing big collections of documents or searching for particular patterns in them.

Topic Models

Regularized Multivariate Analysis Framework for Interpretable High-Dimensional Variable Selection

no code implementations22 Dec 2021 Sergio Muñoz-Romero, Vanessa Gómez-Verdejo, Jerónimo Arenas-García

Multivariate Analysis (MVA) comprises a family of well-known methods for feature extraction which exploit correlations among input variables representing the data.

Variable Selection Vocal Bursts Intensity Prediction

Combinations of Adaptive Filters

no code implementations22 Dec 2021 Jerónimo Arenas-García, Luis A. Azpicueta-Ruiz, Magno T. M. Silva, Vitor H. Nascimento, Ali H. Sayed

Adaptive filters are at the core of many signal processing applications, ranging from acoustic noise supression to echo cancelation, array beamforming, channel equalization, to more recent sensor network applications in surveillance, target localization, and tracking.

Unveiling the semantic structure of text documents using paragraph-aware Topic Models

no code implementations26 Jun 2018 Simón Roca-Sotelo, Jerónimo Arenas-García

Experiments show that this is a proper methodology to highlight certain paragraphs in structured documents at the same time we learn interesting and more diverse topics.

Topic Models

Why (and How) Avoid Orthogonal Procrustes in Regularized Multivariate Analysis

no code implementations9 May 2016 Sergio Muñoz-Romero, Vanessa Gómez-Verdejo, Jerónimo Arenas-García

Multivariate Analysis (MVA) comprises a family of well-known methods for feature extraction that exploit correlations among input variables of the data representation.

Censoring Diffusion for Harvesting WSNs

no code implementations29 Sep 2015 Jesus Fernandez-Bes, Rocío Arroyo-Valles, Jerónimo Arenas-García, Jesús Cid-Sueiro

In this paper, we analyze energy-harvesting adaptive diffusion networks for a distributed estimation problem.

Adaptive Diffusion Schemes for Heterogeneous Networks

no code implementations8 Apr 2015 Jesus Fernandez-Bes, Jerónimo Arenas-García, Magno T. M. Silva, Luis A. Azpicueta-Ruiz

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 some other aspect such as the filter structure or length, or step size.

Sparse Distributed Learning via Heterogeneous Diffusion Adaptive Networks

no code implementations26 Oct 2014 Bijit Kumar Das, Mrityunjoy Chakraborty, Jerónimo Arenas-García

In-network distributed estimation of sparse parameter vectors via diffusion LMS strategies has been studied and investigated in recent years.

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