| Dealing with class imbalance in classifier chains via random undersampling B Liu, G Tsoumakas Knowledge-Based Systems 192, 105292, 2020 | 151 | 2020 |
| Multi-label sampling based on local label imbalance B Liu, K Blekas, G Tsoumakas Pattern Recognition 122, 108294, 2022 | 56 | 2022 |
| Synthetic Oversampling of Multi-Label Data based on Local Label Distribution B Liu, G Tsoumakas Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019 | 40 | 2019 |
| Drug-target interaction prediction via an ensemble of weighted nearest neighbors with interaction recovery B Liu, K Pliakos, C Vens, G Tsoumakas Applied Intelligence, 1-23, 2022 | 32 | 2022 |
| Making classifier chains resilient to class imbalance B Liu, G Tsoumakas 10th Asian Conference on Machine Learning 95, 280-295, 2018 | 28 | 2018 |
| Multiple similarity drug–target interaction prediction with random walks and matrix factorization B Liu, D Papadopoulos, FD Malliaros, G Tsoumakas, AN Papadopoulos Briefings in Bioinformatics 23 (5), bbac353, 2022 | 13 | 2022 |
| Fine-grained selective similarity integration for drug–target interaction prediction B Liu, J Wang, K Sun, G Tsoumakas Briefings in Bioinformatics 24 (2), bbad085, 2023 | 5 | 2023 |
| Integrating Similarities via Local Interaction Consistency and Optimizing Area Under the Curve Measures via Matrix Factorization for Drug-Target Interaction Prediction B Liu, G Tsoumakas IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2024 | 4* | 2024 |
| Multi-label Adaptive Batch Selection by Highlighting Hard and Imbalanced Samples A Zhou, B Liu, Z Peng, J Wang, G Tsoumakas Joint European Conference on Machine Learning and Knowledge Discovery in …, 2024 | 2 | 2024 |
| On the persistence of multilabel learning, its recent trends, and its open issues N Mylonas, I Mollas, B Liu, Y Manolopoulos, G Tsoumakas IEEE Intelligent Systems 38 (2), 28-31, 2023 | 2 | 2023 |
| Local Imbalance based Ensemble for Predicting Interactions between Novel Drugs and Targets B Liu, K Pliakos, G Tsoumakas PharML 2020 (Machine Learning for Pharma and Healthcare Applications …, 2020 | 2 | 2020 |
| Oversampling multi-label data based on natural neighbor and label correlation B Liu, A Zhou, B Wei, J Wang, G Tsoumakas Expert Systems with Applications 259, 125257, 2025 | 1 | 2025 |
| HiGraphDTI: Hierarchical Graph Representation Learning for Drug-Target Interaction Prediction B Liu, S Wu, J Wang, X Deng, A Zhou Joint European Conference on Machine Learning and Knowledge Discovery in …, 2024 | 1 | 2024 |
| Batch Selection for Multi-Label Classification Guided by Uncertainty and Dynamic Label Correlations A Zhou, B Liu, J Wang, G Tsoumakas arXiv preprint arXiv:2412.16521, 2024 | | 2024 |
| AEMLO: AutoEncoder-Guided Multi-label Oversampling A Zhou, B Liu, J Wang, K Sun, K Liu Joint European Conference on Machine Learning and Knowledge Discovery in …, 2024 | | 2024 |
| A Study on Image Reconstruction Based on Decoding fMRI Through Extracting Image Depth Features X Deng, F Bao, B Liu, Y Li, L Zhang International Conference on Neural Computing for Advanced Applications, 449-462, 2024 | | 2024 |
| 基于标签关联的多标签演化超网络 王进， 刘彬， 孙开伟， 陈乔松， 邓欣 电子学报 46 (4), 1012-1018, 2018 | | 2018 |
| 用于微阵列数据分类的子空间融合演化超网络 王进， 刘彬， 张军， 陈乔松， 邓欣 电子学报 44 (10), 2308-2313, 2016 | | 2016 |
Grigorios TsoumakasAristotle University of ThessalonikiVerified email at csd.auth.gr
