Stacking Methods for Hierarchical Classification. - Felipe Kenji Nakano; Saulo Martiello Mastelini; Sylvio Barbon; Ricardo Cerri (ICMLA, 2017)

Top-down strategies for hierarchical classification of transposable elements with neural networks. - Felipe Kenji Nakano; Walter José G. S. Pinto; Gisele Lobo Pappa; Ricardo Cerri (IJCNN, 2017)

Strategies for Selection of Positive and Negative Instances in the Hierarchical Classification of Transposable Elements. - Bruna Zamith Santos; Gean Trindade Pereira; Felipe Kenji Nakano; Ricardo Cerri (BRACIS, 2018)

Improving Hierarchical Classification of Transposable Elements using Deep Neural Networks. - Felipe Kenji Nakano; Saulo Martiello Mastelini; Sylvio Barbon; Ricardo Cerri (IJCNN, 2018)

Hierarchical Classification of Transposable Elements. - Felipe Kenji Nakano; Ricardo Cerri (BNAIC/BENELEARN, 2019)

Machine learning for discovering missing or wrong protein function annotations - A comparison using updated benchmark datasets. - Felipe Kenji Nakano; Mathias Lietaert; Celine Vens (BMC Bioinform., 2019)

Multi-Output Tree Chaining: An Interpretative Modelling and Lightweight Multi-Target Approach. - Saulo Martiello Mastelini; Victor Guilherme Turrisi da Costa; Everton Jose Santana; Felipe Kenji Nakano; Rodrigo Capobianco Guido; Ricardo Cerri; Sylvio Barbon Junior (J. Signal Process. Syst., 2019)

Predictive Bi-clustering Trees for Hierarchical Multi-label Classification. - Bruna Zamith Santos; Felipe Kenji Nakano; Ricardo Cerri; Celine Vens (ECML/PKDD (3), 2020)

Active learning for hierarchical multi-label classification. - Felipe Kenji Nakano; Ricardo Cerri; Celine Vens (Data Min. Knowl. Discov., 2020)

Explaining a Random Survival Forest by Extracting Prototype Rules. - Klest Dedja; Felipe Kenji Nakano; Konstantinos Pliakos; Celine Vens (PKDD/ECML Workshops (2), 2021)

An Adaptive Hybrid Active Learning Strategy with Free Ratings in Collaborative Filtering. - Alireza Gharahighehi; Felipe Kenji Nakano; Celine Vens (IntelliSys (1), 2022)

Explaining random forest prediction through diverse rulesets. - Klest Dedja; Felipe Kenji Nakano; Konstantinos Pliakos; Celine Vens (CoRR, 2022)

Hierarchy exploitation to detect missing annotations on hierarchical multi-label classification. - Miguel Romero 005; Felipe Kenji Nakano; Jorge Finke; Camilo Rocha; Celine Vens (CoRR, 2022)

Deep tree-ensembles for multi-output prediction. - Felipe Kenji Nakano; Konstantinos Pliakos; Celine Vens (Pattern Recognit., 2022)

Active Learning for Survival Analysis with Incrementally Disclosed Label Information. - Klest Dedja; Felipe Kenji Nakano; Celine Vens (IAL@PKDD/ECML, 2023)

BELLATREX: Building Explanations Through a LocaLly AccuraTe Rule EXtractor. - Klest Dedja; Felipe Kenji Nakano; Konstantinos Pliakos; Celine Vens (IEEE Access, 2023)

Leveraging class hierarchy for detecting missing annotations on hierarchical multi-label classification. - Miguel Romero 005; Felipe Kenji Nakano; Jorge Finke; Camilo Rocha; Celine Vens (Comput. Biol. Medicine, 2023)

Online Extra Trees Regressor. - Saulo Martiello Mastelini; Felipe Kenji Nakano; Celine Vens; André Carlos Ponce de Leon Ferreira de Carvalho (IEEE Trans. Neural Networks Learn. Syst., 2023)

Personalized Learning in K-12 Education: Exploring Weak-Labels for a Random Forest-based Collaborative Filtering Approach. - Pedro Ilidio; Alireza Gharahighehi; Felipe Kenji Nakano; Celine Vens (ALL@AIED, 2024)

ITEC at BEA 2024 Shared Task: Predicting Difficulty and Response Time of Medical Exam Questions with Statistical, Machine Learning, and Language Models. - Anaïs Tack; Siem Buseyne; Changsheng Chen; Robbe D'hondt; Michiel De Vrindt; Alireza Gharahighehi; Sameh Metwaly; Felipe Kenji Nakano; Ann-Sophie Noreillie (BEA, 2024)

Deep forests with tree-embeddings and label imputation for weak-label learning. - Pedro Ilidio; Ricardo Cerri; Celine Vens; Felipe Kenji Nakano (IJCNN, 2024)

Predicting adverse long-term neurocognitive outcomes after pediatric intensive care unit admission. - Felipe Kenji Nakano; Karolijn Dulfer; Ilse Vanhorebeek; Pieter J. Wouters; Sascha C. Verbruggen; Koen F. Joosten; Fabian Güiza Grandas; Celine Vens; Greet Van den Berghe (Comput. Methods Programs Biomed., 2024)