149 citations
- Telefonica Research and DevelopmentES18 papers
- Telefonica (Germany)DE9 papers
- Universidad Carlos III de MadridES4 papers
- Universidad Politécnica de MadridES4 papers
- Universitat de BarcelonaES3 papers
- Universitat Politècnica de CatalunyaES3 papers
- Universitat Pompeu FabraES3 papers
- Cyprus University of TechnologyCY2 papers
- Foundation for Research and Technology HellasGR2 papers
- Laboratoire Traitement et Communication de l’InformationFR2 papers
- Universidad Autónoma de MadridES2 papers
- Universidad de ValladolidES2 papers
5 papers · 1 filter
Diffusion Models for Tabular Data Imputation and Synthetic Data Generation
Mario Villaizán-Vallelado, Matteo Salvatori, Carlos Segura +1
Data imputation and data generation have important applications for many domains, like healthcare and finance, where incomplete or missing data can hinder accurate analysis and dec…
Detecting Contextual Network Anomalies with Graph Neural Networks
Hamid Latif-Martínez, José Suárez-Varela, Albert Cabellos-Aparicio +1
Detecting anomalies on network traffic is a complex task due to the massive amount of traffic flows in today's networks, as well as the highly-dynamic nature of traffic over time.…
Rule Extraction in Unsupervised Anomaly Detection for Model Explainability: Application to OneClass SVM
Alberto Barbado, Óscar Corcho, Richard Benjamins
OneClass SVM is a popular method for unsupervised anomaly detection. As many other methods, it suffers from the black box problem: it is difficult to justify, in an intuitive and s…
Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversion
Joan Serrà, Santiago Pascual, Carlos Segura
End-to-end models for raw audio generation are a challenge, specially if they have to work with non-parallel data, which is a desirable setup in many situations. Voice conversion,…
Collaborative Filtering Bandits
Shuai Li, Alexandros Karatzoglou, Claudio Gentile
Classical collaborative filtering, and content-based filtering methods try to learn a static recommendation model given training data. These approaches are far from ideal in highly…