Pablo Pérez-Núñez

12 papers A 1B 1Journal 9Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Self-Supervised Approach for Enhanced Feature Representations in Object Detection Tasks.
CoRR
Santiago C. Vilabella, Pablo Pérez-Núñez, Beatriz Remeseiro
2025 J jnl
Attention-inspired text-based recommender system with explanatory capabilities.
Appl. Soft Comput.
Pablo Pérez-Núñez, Paul Buitelaar, Jorge Díez, Oscar Luaces, Antonio Bahamonde
2025 — conf
Mitigating Overfitting in Recommender Systems via Intra-domain Transfer Learning.
IDEAL (2)
Eva Blanco-Mallo, Pablo Pérez-Núñez, Verónica Bolón-Canedo, Beatriz Remeseiro
2025 J jnl
Towards Explainable Personalized Recommendations by Learning from Users' Photos.
CoRR
Jorge Díez, Pablo Pérez-Núñez, Oscar Luaces, Beatriz Remeseiro, Antonio Bahamonde
2024 B conf
A Self-Supervised Approach for Enhanced Feature Representations in Object Detection Tasks.
IJCNN
Santiago C. Vilabella, Pablo Pérez-Núñez, Beatriz Remeseiro
2023 J jnl
All-in-one picture: visual summary of items in a recommender system.
Neural Comput. Appl.
Pablo Pérez-Núñez, Jorge Díez, Beatriz Remeseiro, Oscar Luaces, Antonio Bahamonde
2023 J jnl
Users' photos of items can reveal their tastes in a recommender system.
Inf. Sci.
Pablo Pérez-Núñez, Jorge Díez, Oscar Luaces, Beatriz Remeseiro, Antonio Bahamonde
2022 J jnl
Correction to: User encoding for clustering in very sparse recommender systems tasks.
Multim. Tools Appl.
Pablo Pérez-Núñez, Jorge Díez, Oscar Luaces, Antonio Bahamonde
2022 J jnl
User encoding for clustering in very sparse recommender systems tasks.
Multim. Tools Appl.
Pablo Pérez-Núñez, Jorge Díez, Oscar Luaces, Antonio Bahamonde
2020 J jnl
Improving recommender systems by encoding items and user profiles considering the order in their consumption history.
Prog. Artif. Intell.
Pablo Pérez-Núñez, Oscar Luaces, Antonio Bahamonde, Jorge Díez
2020 A conf
Taking advantage of images and texts in recommender systems: semantics and explainability.
RecSys
Pablo Pérez-Núñez
2020 J jnl
Towards explainable personalized recommendations by learning from users' photos.
Inf. Sci.
Jorge Díez, Pablo Pérez-Núñez, Oscar Luaces, Beatriz Remeseiro, Antonio Bahamonde