| Support vector machine classifier with pinball loss X Huang, L Shi, J Suykens IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (8), 1279-1291, 2014 | 187 | 2014 |
| Concurrent monitoring of operating condition deviations and process dynamics anomalies with slow feature analysis C Shang, F Yang, X Gao, X Huang, JAK Suykens, D Huang AIChE Journal 61 (11), 3666-3682, 2015 | 169 | 2015 |
| Data-driven robust optimization based on kernel learning C Shang, X Huang, F You Computers & Chemical Engineering 106, 464-479, 2017 | 123 | 2017 |
| Robust multiframe super-resolution employing iteratively re-weighted minimization T Köhler, X Huang, F Schebesch, A Aichert, A Maier, J Hornegger IEEE Transactions on Computational Imaging 2 (1), 42-58, 2016 | 86 | 2016 |
| Learning with the maximum correntropy criterion induced losses for regression Y Feng, X Huang, L Shi, Y Yang, JAK Suykens Journal of Machine Learning Research 16 (1), 993-1034, 2015 | 84 | 2015 |
| Hierarchical minutiae matching for fingerprint and palmprint identification F Chen, X Huang, J Zhou IEEE Transactions on Image Processing 22 (11-12), 4964-4971, 2013 | 73 | 2013 |
| Ramp loss linear programming support vector machine X Huang, L Shi, JAK Suykens Journal of Machine Learning Research 15, 2185−2211, 2014 | 67 | 2014 |
| Robust visual tracking revisited: From correlation filter to template matching F Liu, C Gong, X Huang, T Zhou, J Yang, D Tao IEEE Transactions on Image Processing 27 (6), 2777-2790, 2018 | 58 | 2018 |
| Enhancing dynamic soft sensors based on DPLS: A temporal smoothness regularization approach C Shang, X Huang, JAK Suykens, D Huang Journal of Process Control 28, 17-26, 2015 | 57 | 2015 |
| Indefinite kernels in least squares support vector machines and principal component analysis X Huang, A Maier, J Hornegger, JAK Suykens Applied and Computational Harmonic Analysis 43 (1), 162-172, 2017 | 54 | 2017 |
| Adaptive hinging hyperplanes and its applications in dynamic system identification J Xu, X Huang, S Wang Automatica 45 (10), 2325-2332, 2009 | 53 | 2009 |
| Asymmetric least squares support vector machine classifiers X Huang, L Shi, JAK Suykens Computational Statistics & Data Analysis 70, 395-405, 2014 | 49 | 2014 |
| Random features for kernel approximation: A survey on algorithms, theory, and beyond F Liu, X Huang, Y Chen, JAK Suykens IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 48 | 2021 |
| Varifocal-net: A chromosome classification approach using deep convolutional networks Y Qin, J Wan, H Zheng, X Huang, J Yang, L Wu, N Song, Y Zhu, G Yang IEEE Transactions on Medical Imaging, doi 10.1109/TMI.2019.2905841, 2019 | 40 | 2019 |
| Two-level ℓ1 minimization for compressed sensing X Huang, Y Liu, L Shi, S Van Huffel, JAK Suykens Signal Processing 143, 294-301, 2015 | 39 | 2015 |
| Non-parallel support vector classifiers with different loss functions S Mehrkanoon, X Huang, JAK Suykens Neurocomputing 143, 294-301, 2014 | 36 | 2014 |
| Online PCB defect detector on a new PCB defect dataset S Tang, F He, X Huang, J Yang arXiv preprint arXiv:1902.06197, 2019 | 35 | 2019 |
| Restoration of missing data in limited angle tomography based on Helgason–Ludwig consistency conditions Y Huang, X Huang, O Taubmann, Y Xia, V Haase, J Hornegger, ... Biomedical Physics & Engineering Express 3 (3), 035015, 2017 | 34 | 2017 |
| Sequential minimal optimization for SVM with pinball loss X Huang, L Shi, JAK Suykens Neurocomputing 149, 1596-1603, 2015 | 32 | 2015 |
| Support vector machines with piecewise linear feature mapping X Huang, S Mehrkanoon, JAK Suykens Neurocomputing 117, 118-127, 2013 | 32 | 2013 |
Johan SuykensProfessor, KU LeuvenVerified email at esat.kuleuven.be
