Felipe Kenji Nakano

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 20

Top Topics

Protein Function

Active Learning

Hierarchical Classification

Top Venues

IEEE Trans. Neural Networks Learn. Syst.

Publications

Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
BELLATREX: Building Explanations Through a LocaLly AccuraTe Rule EXtractor. IEEE Access 11 (2023)
Saulo Martiello Mastelini, Felipe Kenji Nakano, Celine Vens, André Carlos Ponce de Leon Ferreira de Carvalho
Online Extra Trees Regressor. IEEE Trans. Neural Networks Learn. Syst. 34 (10) (2023)
Miguel Romero, Felipe Kenji Nakano, Jorge Finke, Camilo Rocha, Celine Vens
Leveraging class hierarchy for detecting missing annotations on hierarchical multi-label classification. Comput. Biol. Medicine 152 (2023)
Klest Dedja, Felipe Kenji Nakano, Celine Vens
Active Learning for Survival Analysis with Incrementally Disclosed Label Information. IAL@PKDD/ECML (2023)
Miguel Romero, Felipe Kenji Nakano, Jorge Finke, Camilo Rocha, Celine Vens
Hierarchy exploitation to detect missing annotations on hierarchical multi-label classification. CoRR (2022)
Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
Explaining random forest prediction through diverse rulesets. CoRR (2022)
Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
Deep tree-ensembles for multi-output prediction. Pattern Recognit. 121 (2022)
Alireza Gharahighehi, Felipe Kenji Nakano, Celine Vens
An Adaptive Hybrid Active Learning Strategy with Free Ratings in Collaborative Filtering. CoRR (2022)
Alireza Gharahighehi, Felipe Kenji Nakano, Celine Vens
An Adaptive Hybrid Active Learning Strategy with Free Ratings in Collaborative Filtering. IntelliSys (1) (2022)
Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
Explaining a Random Survival Forest by Extracting Prototype Rules. PKDD/ECML Workshops (2) (2021)
Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
Deep tree-ensembles for multi-output prediction. CoRR (2020)
Bruna Zamith Santos, Felipe Kenji Nakano, Ricardo Cerri, Celine Vens
Predictive Bi-clustering Trees for Hierarchical Multi-label Classification. ECML/PKDD (3) (2020)
Felipe Kenji Nakano, Ricardo Cerri, Celine Vens
Active learning for hierarchical multi-label classification. Data Min. Knowl. Discov. 34 (5) (2020)
Felipe Kenji Nakano, Ricardo Cerri
Hierarchical Classification of Transposable Elements. BNAIC/BENELEARN (2019)
Felipe Kenji Nakano, Mathias Lietaert, Celine Vens
Machine learning for discovering missing or wrong protein function annotations - A comparison using updated benchmark datasets. BMC Bioinform. 20 (1) (2019)
Saulo Martiello Mastelini, Victor Guilherme Turrisi da Costa, Everton Jose Santana, Felipe Kenji Nakano, Rodrigo Capobianco Guido, Ricardo Cerri, Sylvio Barbon Junior
Multi-Output Tree Chaining: An Interpretative Modelling and Lightweight Multi-Target Approach. J. Signal Process. Syst. 91 (2) (2019)
Bruna Zamith Santos, Gean Trindade Pereira, Felipe Kenji Nakano, Ricardo Cerri
Strategies for Selection of Positive and Negative Instances in the Hierarchical Classification of Transposable Elements. BRACIS (2018)
Felipe Kenji Nakano, Saulo Martiello Mastelini, Sylvio Barbon, Ricardo Cerri
Improving Hierarchical Classification of Transposable Elements using Deep Neural Networks. IJCNN (2018)
Felipe Kenji Nakano, Saulo Martiello Mastelini, Sylvio Barbon, Ricardo Cerri
Stacking Methods for Hierarchical Classification. ICMLA (2017)
Felipe Kenji Nakano, Walter José G. S. Pinto, Gisele Lobo Pappa, Ricardo Cerri
Top-down strategies for hierarchical classification of transposable elements with neural networks. IJCNN (2017)