Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Romano, João M. T."'
Autor:
Brotto, Renan D. B., Loubes, Jean-Michel, Risser, Laurent, Florens, Jean-Pierre, Nose-Filho, Kenji, Romano, João M. T.
We tackle the problem of bias mitigation of algorithmic decisions in a setting where both the output of the algorithm and the sensitive variable are continuous. Most of prior work deals with discrete sensitive variables, meaning that the biases are m
Externí odkaz:
http://arxiv.org/abs/2402.15477
Publikováno v:
In: Deville Y., Gannot S., Mason R., Plumbley M., Ward D. (eds). Latent Variable Analysis and Signal Separation (LVA/ICA 2018). Lecture Notes in Computer Science, vol 10891. Springer, Cham
This work proposes the application of independent component analysis to the problem of ranking different alternatives by considering criteria that are not necessarily statistically independent. In this case, the observed data (the criteria values for
Externí odkaz:
http://arxiv.org/abs/2012.04085
Publikováno v:
In: Torra V., Narukawa Y., Nin J., Agell N. (eds). Modeling Decisions for Artificial Intelligence (MDAI 2020). Lecture Notes in Computer Science, vol 12256. Springer, Cham
In many ranking problems, some particular aspects of the addressed situation should be taken into account in the aggregation process. An example is the presence of correlations between criteria, which may introduce bias in the derived ranking. In the
Externí odkaz:
http://arxiv.org/abs/2012.04091
A number of Multiple Criteria Decision Analysis (MCDA) methods have been developed to rank alternatives based on several decision criteria. Usually, MCDA methods deal with the criteria value at the time the decision is made without considering their
Externí odkaz:
http://arxiv.org/abs/2010.11720
Autor:
Pelegrina, Guilherme D., Brotto, Renan D. B., Duarte, Leonardo T., Attux, Romis, Romano, João M. T.
Publikováno v:
IEEE 2022 International Joint Conference on Neural Networks (IJCNN), 2022, pp. 1-8
In dimensionality reduction problems, the adopted technique may produce disparities between the representation errors of different groups. For instance, in the projected space, a specific class can be better represented in comparison with another one
Externí odkaz:
http://arxiv.org/abs/2006.06137
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Pelegrina, Guilherme D., Brotto, Renan D. B., Duarte, Leonardo T., Attux, Romis, Romano, João M. T.
Publikováno v:
2022 International Joint Conference on Neural Networks (IJCNN).
In dimensionality reduction problems, the adopted technique may produce disparities between the representation errors of different groups. For instance, in the projected space, a specific class can be better represented in comparison with another one
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7efdfb736124df5d468219c7574a239
https://doi.org/10.1109/ijcnn55064.2022.9892809
https://doi.org/10.1109/ijcnn55064.2022.9892809
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.