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Felipe Kenji Nakano
Felipe Kenji Nakano
Post doc Researcher KU Leuven KULAK
在 kuleuven.be 的电子邮件经过验证
标题
引用次数
引用次数
年份
Top-down strategies for hierarchical classification of transposable elements with neural networks
FK Nakano, WJ Pinto, GL Pappa, R Cerri
2017 International joint conference on neural networks (IJCNN), 2539-2546, 2017
442017
Machine learning for discovering missing or wrong protein function annotations: a comparison using updated benchmark datasets
FK Nakano, M Lietaert, C Vens
BMC bioinformatics 20, 1-32, 2019
382019
Active learning for hierarchical multi-label classification
FK Nakano, R Cerri, C Vens
Data Mining and Knowledge Discovery 34 (5), 1496-1530, 2020
362020
Multi-output tree chaining: An interpretative modelling and lightweight multi-target approach
SM Mastelini, VGT da Costa, EJ Santana, FK Nakano, RC Guido, R Cerri, ...
Journal of Signal Processing Systems 91, 191-215, 2019
322019
Online extra trees regressor
SM Mastelini, FK Nakano, C Vens, ACP de Leon Ferreira
IEEE Transactions on Neural Networks and Learning Systems 34 (10), 6755-6767, 2022
302022
Deep tree-ensembles for multi-output prediction
FK Nakano, K Pliakos, C Vens
Pattern Recognition 121, 108211, 2022
232022
Improving hierarchical classification of transposable elements using deep neural networks
FK Nakano, SM Mastelini, S Barbon, R Cerri
2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018
232018
Stacking Methods for Hierarchical Classification
FK Nakano, M Saulo, S Barbon, R Cerri
2017 16th IEEE International Conference on Machine Learning and Applications …, 2017
222017
Strategies for selection of positive and negative instances in the hierarchical classification of transposable elements
BZ Santos, GT Pereira, FK Nakano, R Cerri
2018 7th Brazilian Conference on Intelligent Systems (BRACIS), 420-425, 2018
82018
Proceedings of the International Joint Conference on Neural Networks
FK Nakano, SM Mastelini, S Barbon, R Cerri
IEEE, Rio de Janeiro, 2018
62018
BELLATREX: Building explanations through a locally accurate rule extractor
K Dedja, FK Nakano, K Pliakos, C Vens
Ieee Access 11, 41348-41367, 2023
52023
Predictive bi-clustering trees for hierarchical multi-label classification
BZ Santos, FK Nakano, R Cerri, C Vens
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021
42021
ITEC at BEA 2024 Shared Task: Predicting Difficulty and Response Time of Medical Exam Questions with Statistical, Machine Learning, and Language Models
A Tack, S Buseyne, C Chen, R D’hondt, M De Vrindt, A Gharahighehi, ...
Proceedings of the 19th Workshop on Innovative Use of NLP for Building …, 2024
22024
Leveraging class hierarchy for detecting missing annotations on hierarchical multi-label classification
M Romero, FK Nakano, J Finke, C Rocha, C Vens
Computers in Biology and Medicine 152, 106423, 2023
22023
Explaining a random survival Forest by extracting prototype rules
K Dedja, FK Nakano, K Pliakos, C Vens
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021
22021
Denoising Auto-Encoders as Feature Extractors in Hierarchical Classification Problems
FK Nakano, R Cerri
XIV Encontro Nacional de Inteligência Artificial e Computacional, 2017
22017
Deep forests with tree-embeddings and label imputation for weak-label learning
P Ilidio, R Cerri, C Vens, FK Nakano
2024 International Joint Conference on Neural Networks (IJCNN), 1-8, 2024
12024
Explaining random forest predictions through diverse rules
K Dedja, FK Nakano, K Pliakos, C Vens
arXiv preprint arXiv:2203.15511, 2022
12022
Predicting adverse long-term neurocognitive outcomes after pediatric intensive care unit admission
FK Nakano, K Dulfer, I Vanhorebeek, PJ Wouters, SC Verbruggen, ...
Computer Methods and Programs in Biomedicine 250, 108166, 2024
2024
Deep Forests with Tree-Embeddings and Label Imputation for Weak-Label Learning
P de Carvalho Braga Ilídio, C Vens, R Cerri, FK Nakano
Proceedings of the International Joint Conference on Neural Networks, 2024
2024
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