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pro vyhledávání: '"Filho, Telmo M Silva"'
The principal benefit of unsupervised representation learning is that a pre-trained model can be fine-tuned where data or labels are scarce. Existing approaches for graph representation learning are domain specific, maintaining consistent node and ed
Externí odkaz:
http://arxiv.org/abs/2311.03976
Large graphs are present in a variety of domains, including social networks, civil infrastructure, and the physical sciences to name a few. Graph generation is similarly widespread, with applications in drug discovery, network analysis and synthetic
Externí odkaz:
http://arxiv.org/abs/2306.11412
Autor:
Ferreira-Junior, Manuel, Reinaldo, Jessica T. S., Filho, Telmo M. Silva, Neto, Eufrasio A. Lima, Prudencio, Ricardo B. C.
Item response theory aims to estimate respondent's latent skills from their responses in tests composed of items with different levels of difficulty. Several models of item response theory have been proposed for different types of tasks, such as bina
Externí odkaz:
http://arxiv.org/abs/2303.17731
Akademický článek
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Large graphs are present in a variety of domains, including social networks, civil infrastructure, and the physical sciences to name a few. Graph generation is similarly widespread, with applications in drug discovery, network analysis and synthetic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7639dd2310b19c929a8e3252bea8405b
Akademický článek
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Publikováno v:
Chen, Y, Filho, T M S, Prudêncio, R B C, Diethe, T & Flach, P 2019, β 3-IRT : A New Item Response Model and its Applications . in K Chaudhuri & M Sugiyama (eds), The 22nd International Conference on Artificial Intelligence and Statistics, 16-18 April 2019 . Proceedings of Machine Learning Research, vol. 89, pp. 1013-1021 .
Chen, Y, Filho, T M S, Prudêncio, R B C, Diethe, T & Flach, P 2019, β 3-IRT : A New Item Response Model and its Applications . in K Chaudhuri & M Sugiyama (eds), Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019) : April 16-18, 2019, Naha, Okinawa, Japan . Proceedings of Machine Learning Research, vol. 89, pp. 1013-1021 . < http://proceedings.mlr.press/v89/chen19b.html >
Chen, Y, Filho, T M S, Prudêncio, R B C, Diethe, T & Flach, P 2019, β 3-IRT : A New Item Response Model and its Applications . in K Chaudhuri & M Sugiyama (eds), Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019) : April 16-18, 2019, Naha, Okinawa, Japan . Proceedings of Machine Learning Research, vol. 89, pp. 1013-1021 . < http://proceedings.mlr.press/v89/chen19b.html >
Item Response Theory (IRT) aims to assess latent abilities of respondents based on the correctness of their answers in aptitude test items with different difficulty levels. In this paper, we propose the β3-IRT model, which models continuous response
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a3733a0c7752a729dfda2c4ae16b45a5
https://research-information.bristol.ac.uk/en/publications/3irt(7aa1a29f-28e6-4a68-9a1d-30bbf309d821).html
https://research-information.bristol.ac.uk/en/publications/3irt(7aa1a29f-28e6-4a68-9a1d-30bbf309d821).html
Autor:
Araújo, Marcus, Souza, Renata, Lima, Rita, Filho, Telmo, Araújo, Marcus C, Souza, Renata M C R, Lima, Rita C F, Filho, Telmo M Silva
Publikováno v:
Medical & Biological Engineering & Computing; Jun2017, Vol. 55 Issue 6, p873-884, 12p, 4 Diagrams, 9 Charts, 3 Graphs
Publikováno v:
Neural Information Processing (9783642344862); 2012, p504-511, 8p