| Support vector machines: optimization based theory, algorithms, and extensions N Deng, Y Tian, C Zhang CRC press, 2012 | 669 | 2012 |
| Improvements on twin support vector machines YH Shao, CH Zhang, XB Wang, NY Deng IEEE transactions on neural networks 22 (6), 962-968, 2011 | 593 | 2011 |
| A new method of data mining-support vector machine N Deng, Y Tian Science Publication, Beijing City 51, 2004 | 573 | 2004 |
| iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins Y Xu, XJ Shao, LY Wu, NY Deng, KC Chou PeerJ 1, e171, 2013 | 309 | 2013 |
| Nonmonotonic trust region algorithm NY Deng, Y Xiao, FJ Zhou Journal of optimization theory and applications 76, 259-285, 1993 | 309 | 1993 |
| New quasi-Newton equation and related methods for unconstrained optimization JZ Zhang, NY Deng, LH Chen Journal of Optimization Theory and Applications 102 (1), 147-167, 1999 | 276 | 1999 |
| iNitro-Tyr: Prediction of nitrotyrosine sites in proteins with general pseudo amino acid composition Y Xu, X Wen, LS Wen, LY Wu, NY Deng, KC Chou PloS one 9 (8), e105018, 2014 | 269 | 2014 |
| iHyd-PseAAC: predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid composition Y Xu, X Wen, XJ Shao, NY Deng, KC Chou International journal of molecular sciences 15 (5), 7594-7610, 2014 | 237 | 2014 |
| An efficient weighted Lagrangian twin support vector machine for imbalanced data classification YH Shao, WJ Chen, JJ Zhang, Z Wang, NY Deng Pattern Recognition 47 (9), 3158-3167, 2014 | 176 | 2014 |
| Nonparallel hyperplane support vector machine for binary classification problems YH Shao, WJ Chen, NY Deng Information Sciences 263, 22-35, 2014 | 169 | 2014 |
| Drug repositioning by kernel-based integration of molecular structure, molecular activity, and phenotype data Y Wang, S Chen, N Deng, Y Wang PloS one 8 (11), e78518, 2013 | 161 | 2013 |
| Least squares recursive projection twin support vector machine for classification YH Shao, NY Deng, ZM Yang Pattern Recognition 45 (6), 2299-2307, 2012 | 150 | 2012 |
| An ε-twin support vector machine for regression YH Shao, CH Zhang, ZM Yang, L Jing, NY Deng Neural Computing and Applications 23, 175-185, 2013 | 144 | 2013 |
| MLTSVM: A novel twin support vector machine to multi-label learning WJ Chen, YH Shao, CN Li, NY Deng Pattern Recognition 52, 61-74, 2016 | 140 | 2016 |
| A regularization for the projection twin support vector machine YH Shao, Z Wang, WJ Chen, NY Deng Knowledge-Based Systems 37, 203-210, 2013 | 114 | 2013 |
| Twin support vector machine for clustering Z Wang, YH Shao, L Bai, NY Deng IEEE transactions on neural networks and learning systems 26 (10), 2583-2588, 2015 | 109 | 2015 |
| A coordinate descent margin based-twin support vector machine for classification YH Shao, NY Deng Neural networks 25, 114-121, 2012 | 106 | 2012 |
| Robust L1-norm two-dimensional linear discriminant analysis CN Li, YH Shao, NY Deng Neural Networks 65, 92-104, 2015 | 99 | 2015 |
| Prediction of palmitoylation sites using the composition of k-spaced amino acid pairs XB Wang, LY Wu, YC Wang, NY Deng Protein Engineering, Design & Selection 22 (11), 707-712, 2009 | 92 | 2009 |
| Weighted linear loss twin support vector machine for large-scale classification YH Shao, WJ Chen, Z Wang, CN Li, NY Deng Knowledge-Based Systems 73, 276-288, 2015 | 89 | 2015 |
