Zobrazeno 1 - 10
of 254
pro vyhledávání: '"Vicente, Renato"'
Autor:
Polo, Felipe Maia, Izbicki, Rafael, Lacerda Jr, Evanildo Gomes, Ibieta-Jimenez, Juan Pablo, Vicente, Renato
Publikováno v:
Information Sciences (2023): 119612
Supervised learning techniques typically assume training data originates from the target population. Yet, in reality, dataset shift frequently arises, which, if not adequately taken into account, may decrease the performance of their predictors. In t
Externí odkaz:
http://arxiv.org/abs/2205.08340
Autor:
Polo, Felipe Maia, Mendonça, Gabriel Caiaffa Floriano, Parreira, Kauê Capellato J., Gianvechio, Lucka, Cordeiro, Peterson, Ferreira, Jonathan Batista, de Lima, Leticia Maria Paz, Maia, Antônio Carlos do Amaral, Vicente, Renato
We present and make available pre-trained language models (Phraser, Word2Vec, Doc2Vec, FastText, and BERT) for the Brazilian legal language, a Python package with functions to facilitate their use, and a set of demonstrations/tutorials containing som
Externí odkaz:
http://arxiv.org/abs/2110.15709
Autor:
Toledo, Carmen Melo, Bassedon, Guilherme Mendes, Ferreira, Jonathan Batista, Gianvechio, Lucka de Godoy, Guatimosim, Carlos, Polo, Felipe Maia, Vicente, Renato
Student's grade retention is a key issue faced by many education systems, especially those in developing countries. In this paper, we seek to gauge the relevance of students' personality traits in predicting grade retention in Brazil. For that, we us
Externí odkaz:
http://arxiv.org/abs/2107.05767
Autor:
Vilarino, Ramon, Vicente, Renato
We dissect an experimental credit scoring model developed with real data and demonstrate - without access to protected attributes - how the use of location information introduces racial bias. We analyze the tree gradient boosting model with the aid o
Externí odkaz:
http://arxiv.org/abs/2011.09865
Autor:
Polo, Felipe Maia, Vicente, Renato
In supervised learning, training and test datasets are often sampled from distinct distributions. Domain adaptation techniques are thus required. Covariate shift adaptation yields good generalization performance when domains differ only by the margin
Externí odkaz:
http://arxiv.org/abs/2010.01184
Autor:
Veiga, Rodrigo, Vicente, Renato
We explore alternative experimental setups for the iterative sampling (flow) from Restricted Boltzmann Machines (RBM) mapped on the temperature space of square lattice Ising models by a neural network thermometer. This framework has been introduced t
Externí odkaz:
http://arxiv.org/abs/2006.10176
We sample aggravated cases following age-structured probabilities from confirmed cases and use ICU occupation data to find a subnotification factor. A logistic fit is then employed to project the progression of the COVID-19 epidemic with plateau scen
Externí odkaz:
http://arxiv.org/abs/2006.06530
Autor:
Maia Polo, Felipe, Izbicki, Rafael, Lacerda, Evanildo Gomes, Jr, Ibieta-Jimenez, Juan Pablo, Vicente, Renato
Publikováno v:
In Information Sciences November 2023 649
Autor:
Maia Polo, Felipe1 (AUTHOR) felipemaiapolo@gmail.com, Vicente, Renato2 (AUTHOR)
Publikováno v:
Neural Computing & Applications. Sep2023, Vol. 35 Issue 25, p18187-18199. 13p.
Autor:
Arlete Gianfaldoni, Cristiane Roa, Ricardo dos Santos Simões, Maria Cândida P. Baracat, Angela Maggio da Fonseca, Vicente Renato Bagnoli, Isabel Cristina Espósito Sopreso, Fernando Wladimir Silva Rivas, Pedro Monteleone, Edmund C. Baracat, José Maria Soares Júnior
Publikováno v:
PLoS ONE, Vol 18, Iss 12 (2023)
Externí odkaz:
https://doaj.org/article/e91115de18ad45008486febe45b4301e