no code implementations • 13 Jul 2022 • Miguel Romero, Felipe Kenji Nakano, Jorge Finke, Camilo Rocha, Celine Vens
The availability of genomic data has grown exponentially in the last decade, mainly due to the development of new sequencing technologies.
no code implementations • 29 Mar 2022 • Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
In this work we propose a novel method that is Building Explanations through a LocalLy AccuraTe Rule EXtractor (Bellatrex), and is able to explain the forest prediction for a given test instance with only a few diverse rules.
no code implementations • 11 Mar 2022 • Alireza Gharahighehi, Felipe Kenji Nakano, Celine Vens
This rating elicitation procedure enriches the interaction matrix with informative ratings and therefore assists the recommender system to better model the preferences of the users.
no code implementations • 3 Nov 2020 • Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
In this paper, we specifically focus on two structured output prediction tasks, namely multi-label classification and multi-target regression.