| Model-based kernel for efficient time series analysis H Chen, F Tang, P Tino, X Yao Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013 | 113 | 2013 |
| Learning joint space–time–frequency features for EEG decoding on small labeled data D Zhao, F Tang, B Si, X Feng Neural Networks 114, 67-77, 2019 | 56 | 2019 |
| Model metric co-learning for time series classification H Chen, F Tang, P Tino, AG Cohn, X Yao Twenty-fourth international joint conference on artificial intelligence, 2015 | 56 | 2015 |
| Feature selection with kernelized multi-class support vector machine Y Guo, Z Zhang, F Tang Pattern Recognition 117, 107988, 2021 | 46 | 2021 |
| Group feature selection with multiclass support vector machine F Tang, L Adam, B Si Neurocomputing 317, 42-49, 2018 | 28 | 2018 |
| Liver cancer identification based on PSO-SVM model H Jiang, F Tang, X Zhang 2010 11th International Conference on Control Automation Robotics & Vision …, 2010 | 17 | 2010 |
| Generalized learning Riemannian space quantization: A case study on Riemannian manifold of SPD matrices F Tang, M Fan, P Tiňo IEEE transactions on neural networks and learning systems 32 (1), 281-292, 2020 | 16 | 2020 |
| NeuroBayesSLAM: Neurobiologically inspired Bayesian integration of multisensory information for robot navigation T Zeng, F Tang, D Ji, B Si Neural Networks 126, 21-35, 2020 | 15 | 2020 |
| Ordinal regression based on learning vector quantization F Tang, P Tiňo Neural Networks 93, 76-88, 2017 | 13 | 2017 |
| The benefits of modeling slack variables in svms F Tang, P Tiňo, PA Gutiérrez, H Chen Neural computation 27 (4), 954-981, 2015 | 10 | 2015 |
| Parameters optimization in SVM based-on ant colony optimization algorithm XY Liu, HY Jiang, FZ Tang Advanced materials research 121, 470-475, 2010 | 10 | 2010 |
| Learning the deterministically constructed echo state networks F Tang, P Tiňo, H Chen 2014 International Joint Conference on Neural Networks (IJCNN), 77-83, 2014 | 7 | 2014 |
| Probabilistic learning vector quantization on manifold of symmetric positive definite matrices F Tang, H Feng, P Tino, B Si, D Ji Neural Networks 142, 105-118, 2021 | 5 | 2021 |
| Scan registration for underwater mechanical scanning imaging sonar using symmetrical Kullback–Leibler divergence M Jiang, S Song, F Tang, Y Li, J Liu, X Feng Journal of Electronic Imaging 28 (1), 013026-013026, 2019 | 4 | 2019 |
| Support Vector Ordinal Regression using Privileged Information. F Tang, P Tino, PA Gutiérrez, H Chen ESANN, 2014 | 3 | 2014 |
| A novel oversampling technique based on the manifold distance for class imbalance learning Y Guo, B Jiao, L Yang, J Cheng, S Yang, F Tang International Journal of Bio-Inspired Computation 18 (3), 131-142, 2021 | 2 | 2021 |
| Unsupervised feature learning for visual place recognition in changing environments D Zhao, B Si, F Tang 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 2 | 2019 |
| Nonstationary fuzzy neural network based on FCMnet clustering and a modified CG method with Armijo-type rule B Zhang, X Gong, J Wang, F Tang, K Zhang, W Wu Information Sciences 608, 313-338, 2022 | 1 | 2022 |
| Machine-Learning-Based Olfactometry: Odor Descriptor Clustering Analysis for Olfactory Perception Prediction of Odorant Molecules L Shang, C Liu, F Tang, B Chen, L Liu, K Hayashi | 1 | 2022 |
| Model learning based on grid cell representations G Huang, B Si, F Tang 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO), 1032 …, 2017 | 1 | 2017 |
