Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Lavra, Nada"'
The increasing amounts of semantic resources offer valuable storage of human knowledge; however, the probability of wrong entries increases with the increased size. The development of approaches that identify potentially spurious parts of a given kno
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aceeb8b8d0b0b187bcb1a8e30df477ae
http://arxiv.org/abs/2111.11710
http://arxiv.org/abs/2111.11710
Feature ranking has been widely adopted in machine learning applications such as high-throughput biology and social sciences. The approaches of the popular Relief family of algorithms assign importances to features by iteratively accounting for neare
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::238e178df09e6f3dd243fb18452bc71c
Black-box neural network models are widely used in industry and science, yet are hard to understand and interpret. Recently, the attention mechanism was introduced, offering insights into the inner workings of neural language models. This paper explo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddd13282fec68ad89e8bf52aac3027e1
Publikováno v:
AI Communications: The European Journal on Artificial Intelligence; January 1996, Vol. 9 Issue: 4 p157-206, 50p
Autor:
Lavra, Nada, De Raedt, Luc
Publikováno v:
AI Communications: The European Journal on Artificial Intelligence; January 1995, Vol. 8 Issue: 1 p3-19, 17p
Publikováno v:
Journal of Chemical Information and Modeling; November 1997, Vol. 37 Issue: 6 p966-970, 5p