Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Francesco Epifania"'
Autor:
Sahar Shah, Sara Lucia Manzoni, Farooq Zaman, Fatima Es Sabery, Francesco Epifania, Italo Francesco Zoppis
Publikováno v:
IEEE Access, Vol 12, Pp 104964-104982 (2024)
Continual learning (CL) with bidirectional encoder representation from transformer (BERT) and its variant Distil-BERT, have shown remarkable performance in various natural language processing (NLP) tasks, such as text classification (TC). However, th
Externí odkaz:
https://doaj.org/article/7cbd432fe159472d8e395156567d20bf
Publikováno v:
Italian Journal of Educational Technology, Vol 22, Iss 2 (2014)
In queste pagine si introduce una piattaforma a servizio degli usuali Learning Management Systems (LMS) per consentirne un utilizzo facile e proficuo da parte dei docenti di un determinato settore. Nello specifico la piattaforma costituisce il suppor
Externí odkaz:
https://doaj.org/article/a8fb98924b624395b6d9428294cecd6e
Autor:
Francesco Epifania, Alberto Schiaffino, Ict Startup, Serena Di Gaetano, Bruno Apolloni, Luca Marconi, Stefano Valtolina, Web Agency, Marco Mesiti, Roberto Pellegrini
Publikováno v:
Journal of Business and Economics. 10:287-301
We discuss a Cloud-based Collective Intelligence model and its in-progress implementation to direct users toward an optimal usage of their home appliances as a way of getting both personal advantage and an overall reduction of pollution and energy co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::140618ea2658315b683fed3fe140057f
https://doi.org/10.15341/jbe(2155-7950)/04.10.2019/003
https://doi.org/10.15341/jbe(2155-7950)/04.10.2019/003
Autor:
Sara Manzoni, Giancarlo Mauri, Luca Marconi, Italo Zoppis, Ricardo Anibal Matamoros Aragon, Francesco Epifania
Publikováno v:
AIxIA 2020 – Advances in Artificial Intelligence ISBN: 9783030770907
AI*IA
AI*IA
Learning and training processes are starting to be affected by the diffusion of Artificial Intelligence (AI) techniques and methods. AI can be variously exploited for supporting education, though especially deep learning (DL) models are normally suff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e5ad1bd7925f3addf2f35821b7068c1
https://doi.org/10.1007/978-3-030-77091-4_5
https://doi.org/10.1007/978-3-030-77091-4_5
Autor:
Francesco Epifania, Giancarlo Mauri, Sara Manzoni, Luca Marconi, Ricardo Anibal Matamoros Aragon, Italo Zoppis
Publikováno v:
Scopus-Elsevier
CSEDU (1)
CSEDU (1)
Recent studies in the context of machine learning have shown the effectiveness of deep attentional mechanisms for identifying important communities and relationships within a given input network. These studies can be effectively applied in those cont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d978b38611a0c5eb06b35d14b8d796e0
http://hdl.handle.net/10281/279017
http://hdl.handle.net/10281/279017
Autor:
Italo Zoppis, Luca Marconi, Riccardo Dondi, Giancarlo Mauri, Sara Manzoni, Francesco Epifania
Publikováno v:
CSEDU (1)
Scopus-Elsevier
Scopus-Elsevier
Recommender Systems have became extremely appealing for all technology enhanced learning researches aimed to design, develop and test technical innovations which support and enhance learning and teaching practices of both individuals and organization
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc802a4087e0600c6b3f0af154084974
https://doi.org/10.5220/0007749500850091
https://doi.org/10.5220/0007749500850091
Autor:
Francesco Epifania, Riccardo Porrini
Publikováno v:
CSEDU (1)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a68ef0d049d78d4c18acaf5b5ccc9c1
https://doi.org/10.5220/0005810903760382
https://doi.org/10.5220/0005810903760382
Publikováno v:
Advances in Neural Networks ISBN: 9783319337463
Advances in Neural Networks
Advances in Neural Networks
We introduce a new recommending paradigm based on the genomic features of the candidate objects. The system is based on the tree structure of the object metadata which we convert in acceptance rules, leaving the user the discretion of selecting the m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92e4abf158c8fc6d98c6a9c4bc1f4574
https://doi.org/10.1007/978-3-319-33747-0_9
https://doi.org/10.1007/978-3-319-33747-0_9