Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Rabhi, Sara"'
Recently, large language models (LLMs) have exhibited significant progress in language understanding and generation. By leveraging textual features, customized LLMs are also applied for recommendation and demonstrate improvements across diverse recom
Externí odkaz:
http://arxiv.org/abs/2311.02089
Synthetic data and simulators have the potential to markedly improve the performance and robustness of recommendation systems. These approaches have already had a beneficial impact in other machine-learning driven fields. We identify and discuss a ke
Externí odkaz:
http://arxiv.org/abs/2112.11022
Session-based recommendation is an important task for e-commerce services, where a large number of users browse anonymously or may have very distinct interests for different sessions. In this paper we present one of the winning solutions for the Reco
Externí odkaz:
http://arxiv.org/abs/2107.05124
Autor:
Rabhi, Sara, Blanchard, Frédéric, Diallo, Alpha Mamadou, Zeghlache, Djamal, Lukas, Céline, Berot, Aurélie, Delemer, Brigitte, Barraud, Sara
Publikováno v:
In Artificial Intelligence In Medicine November 2022 133
Autor:
Rabhi, Sara
The wide adoption of Electronic Health Records in hospitals’ information systems has led to the definition of large databases grouping various types of data such as textual notes, longitudinal medical events, and tabular patient information. Howeve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______166::eb31ecd1bcb16b516c182b710306ba2c
https://theses.hal.science/tel-03600526
https://theses.hal.science/tel-03600526
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
ACM International Conference Proceeding Series; 9/20/2019, p1-5, 5p