Zobrazeno 1 - 10
of 316
pro vyhledávání: '"Alonso‐Betanzos, Amparo"'
Autor:
Fernández-Campa-González, Álvaro, Paz-Ruza, Jorge, Alonso-Betanzos, Amparo, Guijarro-Berdiñas, Bertha
Among the existing approaches for visual-based Recommender System (RS) explainability, utilizing user-uploaded item images as efficient, trustable explanations is a promising option. However, current models following this paradigm assume that, for an
Externí odkaz:
http://arxiv.org/abs/2407.06740
Dietary Restriction (DR) is one of the most popular anti-ageing interventions, prompting exhaustive research into genes associated with its mechanisms. Recently, Machine Learning (ML) has been explored to identify potential DR-related genes among age
Externí odkaz:
http://arxiv.org/abs/2406.09898
Autor:
Paz-Ruza, Jorge, Alonso-Betanzos, Amparo, Guijarro-Berdiñas, Bertha, Cancela, Brais, Eiras-Franco, Carlos
Dyadic regression models, which predict real-valued outcomes for pairs of entities, are fundamental in many domains (e.g. predicting the rating of a user to a product in Recommender Systems) and promising and under exploration in many others (e.g. ap
Externí odkaz:
http://arxiv.org/abs/2401.10690
Autor:
Rodríguez-Arias, Alejandro, Alonso-Betanzos, Amparo, Guijarro-Berdiñas, Bertha, Sánchez-Marroño, Noelia
Compartmental epidemiological models categorize individuals based on their disease status, such as the SEIRD model (Susceptible-Exposed-Infected-Recovered-Dead). These models determine the parameters that influence the magnitude of an outbreak, such
Externí odkaz:
http://arxiv.org/abs/2307.15723
Autor:
Paz-Ruza, Jorge, Alonso-Betanzos, Amparo, Guijarro-Berdiñas, Berta, Cancela, Brais, Eiras-Franco, Carlos
Recommender Systems have become crucial in the modern world, commonly guiding users towards relevant content or products, and having a large influence over the decisions of users and citizens. However, ensuring transparency and user trust in these sy
Externí odkaz:
http://arxiv.org/abs/2308.01196
Autor:
Botana, Iñigo López-Riobóo, Eiras-Franco, Carlos, Hernandez-Castro, Julio, Alonso-Betanzos, Amparo
Most proposals in the anomaly detection field focus exclusively on the detection stage, specially in the recent deep learning approaches. While providing highly accurate predictions, these models often lack transparency, acting as "black boxes". This
Externí odkaz:
http://arxiv.org/abs/2209.04173
Autor:
Fumanal-Idocin, Javier, Cordón, Oscar, Minárová, María, Alonso-Betanzos, Amparo, Bustince, Humberto
Publikováno v:
Fumanal Idocin, J., Cordon, O., Min\'arov\'a, M., Alonso Betanzos, A., & Bustince, H. (2022). Combinations of Affinity Functions for Different Community Detection Algorithms in Social Networks
Social network analysis is a popular discipline among the social and behavioural sciences, in which the relationships between different social entities are modelled as a network. One of the most popular problems in social network analysis is finding
Externí odkaz:
http://arxiv.org/abs/2208.12874
Autor:
Botana, Iñigo López-Riobóo, Bolón-Canedo, Verónica, Guijarro-Berdiñas, Bertha, Alonso-Betanzos, Amparo
There are many contexts in which dyadic data are present. Social networks are a well-known example. In these contexts, pairs of elements are linked building a network that reflects interactions. Explaining why these relationships are established is e
Externí odkaz:
http://arxiv.org/abs/2205.01759
Publikováno v:
In Neurocomputing 28 September 2024 599