N. Deng

Yingjie Tian, Zhixia Yang, Naiyang Deng, 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

A New Support Vector Machine for Multi-class Classification

Zhiquan Qi, Yingjie Tian, Naiyang Deng, 2005, The Fifth International Conference on Computer and Information Technology (CIT'05).

A Family of Scaled Factorized Broyden-Like Methods for Nonlinear Least Squares Problems

Naiyang Deng, L. H. Chen, Jianzhong Zhang, 1999, SIAM J. Optim..

Network predicting drug's anatomical therapeutic chemical code

Yong Wang, Nai-Yang Deng, Yong-Cui Wang, 2013, Bioinform..

New robust unsupervised support vector machines

Kun Zhao, Mingyu Zhang, Naiyang Deng, 2011, J. Syst. Sci. Complex..

Robust Unsupervised and Semisupervised Bounded C-Support Vector Machines

Kun Zhao, Yingjie Tian, Naiyang Deng, 2007, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007).

Generalized two-dimensional linear discriminant analysis with regularization pdf

Yuan-Hai Shao, Chun-Na Li, Nai-Yang Deng, 2018, Neural Networks.

Robust 2DPCA by Tℓ₁ Criterion Maximization for Image Recognition

Liming Liu, Wensi Wang, Liting Zhang, 2021, IEEE Access.

Principal Component Analysis Based on T$\ell_1$-norm Maximization

Yuan-Hai Shao, Chun-Na Li, Nai-Yang Deng, 2020, 2005.12263.

2DRLPP: Robust two-dimensional locality preserving projection with regularization

Yuan-Hai Shao, Chun-Na Li, Ju Zhang, 2019, Knowl. Based Syst..

The new interpretation of support vector machines on statistical learning theory

Chunhua Zhang, Nai-Yang Deng, Yingjie Tian, 2010 .

Lysine acetylation sites prediction using an ensemble of support vector machine classifiers.

Jun Ding, Yan Xu, Nai-Yang Deng, 2010, Journal of theoretical biology.

Probabilistic outputs for twin support vector machines

Yuan-Hai Shao, Zhen Wang, Nai-Yang Deng, 2012, Knowl. Based Syst..

Gene expression variations are predictive for stochastic noise

Zhaolei Zhang, N. Deng, Xiaojian Shao, 2010, Nucleic Acids Res..

A regression framework incorporating quantitative and negative interaction data improves quantitative prediction of PDZ domain–peptide interaction from primary sequence

Gary D. Bader, Gary D Bader, Naiyang Deng, 2010, Bioinform..

Prediction of protein methylation sites using conditional random field.

Yan Xu, Nai-Yang Deng, Yan Xu, 2012, Protein and peptide letters.

Distinguishing enzymes from non-enzymes via support vector machine

Nai-Yang Deng, N. Deng, Yong-Cui Wang, 2008 .

Mixed-norm linear support vector machine

N. Deng, Y. Shao, Chunhua Zhang, 2013, Neural Computing and Applications.

Nai-Yang Deng, N. Deng, Chunhua Zhang, 2010 .

A Novel SVM-RFE for Gene Selection∗

N. Deng, Junyan Tan, Zhixia Yang, 2009 .

Adaptive feature selection via a new version of support vector machine

N. Deng, Chunhua Zhang, Junyan Tan, 2013, Neural Computing and Applications.

Prediction of enzyme subfamily class via pseudo amino acid composition by incorporating the conjoint triad feature.

Nai-Yang Deng, Zhi-Xia Yang, Yong-Cui Wang, 2010, Protein and peptide letters.

Computational probing protein-protein interactions targeting small molecules

Yong Wang, Nai-Yang Deng, Yong-Cui Wang, 2015, Bioinform..

Novel Grouping Method-based support vector machine plus for structured data

Ling Zhen, Qiuling Hou, Naiyang Deng, 2016, Neurocomputing.

Improvements on Twin Support Vector Machines

Yuan-Hai Shao, Chunhua Zhang, Nai-Yang Deng, 2011, IEEE Transactions on Neural Networks.

Weighted Lagrange ε-twin support vector regression

Lan Bai, Yuan-Hai Shao, Zhen Wang, 2016, Neurocomputing.

Nonparallel hyperplane support vector machine for binary classification problems

Yuan-Hai Shao, Nai-Yang Deng, Wei-Jie Chen, 2014, Inf. Sci..

Least squares recursive projection twin support vector machine for classification

Yuan-Hai Shao, Nai-Yang Deng, Zhi-Min Yang, 2012, Pattern Recognit..

Robust L1-norm two-dimensional linear discriminant analysis

Yuan-Hai Shao, Chun-Na Li, Nai-Yang Deng, 2015, Neural Networks.

Constructing support vector machine ensemble with segmentation for imbalanced datasets

Ling Jing, N. Deng, Bing Yang, 2013, Neural Computing and Applications.

Ν-projection Twin Support Vector Machine for Pattern Classification

Yuan-Hai Shao, Chun-Na Li, Zhen Wang, 2020, Neurocomputing.

The Best Separating Decision Tree Twin Support Vector Machine for Multi-Class Classification

Yuan-Hai Shao, Wei-Jie Chen, Zhi-Min Yang, 2013, ITQM.

A novel margin-based twin support vector machine with unity norm hyperplanes

N. Deng, Y. Shao, 2013, Neural Computing and Applications.

Sparse Lq-norm least squares support vector machine with feature selection

Yuan-Hai Shao, Chun-Na Li, Zhen Wang, 2018, Pattern Recognit..

Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions

Nai-Yang Deng, Yingjie Tian, Chunhua Zhang, 2012 .

An efficient weighted Lagrangian twin support vector machine for imbalanced data classification

Yuan-Hai Shao, Zhen Wang, Nai-Yang Deng, 2014, Pattern Recognit..

Predicting DNA- and RNA-binding proteins from sequences with kernel methods.

Ling Jing, Lingyun Wu, Xiaojian Shao, 2009, Journal of theoretical biology.

MLTSVM: A novel twin support vector machine to multi-label learning

Yuan-Hai Shao, Chun-Na Li, Nai-Yang Deng, 2016, Pattern Recognit..

Least squares twin parametric-margin support vector machine for classification

N. Deng, Y. Shao, Wei-Jie Chen, 2013, Applied Intelligence.

Sparse least square twin support vector machine with adaptive norm

N. Deng, Junyan Tan, Ling Zhen, 2014, Applied Intelligence.

Prediction of posttranslational modification sites from amino acid sequences with kernel methods.

Yan Xu, Ling-Yun Wu, Yingjie Tian, 2014, Journal of theoretical biology.

A novel feature selection method for twin support vector machine

Lan Bai, Yuan-Hai Shao, Zhen Wang, 2014, Knowl. Based Syst..

Multiple Flat Projections for Cross-Manifold Clustering

N. Deng, Y. Shao, Lan Bai, 2020, IEEE Transactions on Cybernetics.

Robust Bhattacharyya bound linear discriminant analysis through adaptive algorithm

Yuan-Hai Shao, Chun-Na Li, Zhen Wang, 2018, ArXiv.

New Unsupervised Support Vector Machines

Kun Zhao, Nai-Yang Deng, Yingjie Tian, 2009 .

Robust Unsupervised Lagrangian Support Vector Machines for Supply Chain Management

Kun Zhao, Naiyang Deng, Yong-sheng Liu, 2009 .

Single and Union Non-Parallel Support Vector Machine Frameworks pdf

Yuan-Hai Shao, Chun-Na Li, Nai-Yang Deng, 2019, SSRN Electronic Journal.

Single Versus Union: Non-parallel Support Vector Machine Frameworks

N. Xiu, N. Deng, Y. Shao, 2019, ArXiv.

An Efficient Version on a New Improved Method of Tangent Hyperbolas

Haibin Zhang, Qiang Cheng, Naiyang Deng, 2007, LSMS.

Theoretical efficiency of a new inexact method of tangent hyperbolas

Haibin Zhang, Naiyang Deng, Haibin Zhang, 2004, Optim. Methods Softw..

Sequence-based protein-protein interaction prediction via support vector machine

Nai-Yang Deng, Zhixia Yang, Jiguang Wang, 2010, J. Syst. Sci. Complex..

On the symmetric rank-m correction of matrices

Meifang Zhu, Naiyang Deng, N. Deng, 1989 .

A theoretical analysis on efficiency of some Newton-PCG methods

Jianzhon Zhang, P. Zhong, N. Deng, 2005 .

Kernel-based data fusion improves the drug-protein interaction prediction

Chunhua Zhang, Yong Wang, Nai-Yang Deng, 2011, Comput. Biol. Chem..

Support Vector Classification with Nominal Attributes

Yingjie Tian, Naiyang Deng, Ying-jie Tian, 2005, CIS.

Robust L1-norm multi-weight vector projection support vector machine with efficient algorithm

Yuan-Hai Shao, Chun-Na Li, Wei-Jie Chen, 2018, Neurocomputing.

Twin Support Vector Machine for Clustering

Lan Bai, Yuan-Hai Shao, Zhen Wang, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Robust bilateral Lp-norm two-dimensional linear discriminant analysis

Yuan-Hai Shao, Chun-Na Li, Nai-Yang Deng, 2019, Inf. Sci..

Union nonparallel support vector machines framework with consistency

N. Xiu, N. Deng, Y. Shao, 2023, Appl. Soft Comput..

Locality Sensitive Proximal Classifier with Consistency for Small Sample Size Problem

Yuan-Hai Shao, Chun-Na Li, Zhen Wang, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

Proximal Classifier via Absolute Value Inequalities

Yuan-Hai Shao, Chun-Na Li, Zhen Wang, 2014, 2014 IEEE International Conference on Data Mining Workshop.

A coordinate descent margin based-twin support vector machine for classification

Yuan-Hai Shao, Nai-Yang Deng, N. Deng, 2012, Neural Networks.

Modified Partial-Update Newton-Type Algorithms for Unary Optimization

N. Deng, L. Chen, Jianzhong Zhang, 1998 .

Computationally Probing Drug-Protein Interactions Via Support Vector Machine

Yong Wang, Nai-Yang Deng, Zhi-Xia Yang, 2010 .

An Inexact Newton Method Derived from Efficiency Analysis

Ping Zhong, Naiyang Deng, Jianzhong Zhang, 2005, J. Glob. Optim..

Theoretical Efficiency of an Inexact Newton Method

Z. Z. Wang, N. Deng, N. Y. Deng, 2000 .

Unsupervised Support Vector Machines with Perturbations

N. Deng, X. Kong, Kun Zhao, 2008, 2008 Second International Symposium on Intelligent Information Technology Application.

Improving accuracy of protein-protein interaction prediction by considering the converse problem for sequence representation

Xiang-Sun Zhang, Yong Wang, Nai-Yang Deng, 2011, BMC Bioinformatics.

Prediction of Protein-Protein Interaction Based Only on Coding Sequences

Nai-Yang Deng, Zhi-Xia Yang, Jiguang Wang, 2009 .

Extensive semi-quantitative regression

Yuan-Hai Shao, Nai-Yang Deng, Ya-Fen Ye, 2016, Neurocomputing.

Manifold proximal support vector machine with mixed-norm for semi-supervised classification

N. Deng, Junyan Tan, Ling Zhen, 2015, Neural Computing and Applications.

Laplacian least squares twin support vector machine for semi-supervised classification

Yuan-Hai Shao, Wei-Jie Chen, Nai-Yang Deng, 2014, Neurocomputing.

Laplacian p-norm proximal support vector machine for semi-supervised classification

Zhiqiang Zhang, Ling Zhen, Naiyang Deng, 2014, Neurocomputing.

Laplacian unit-hyperplane learning from positive and unlabeled examples

Yuan-Hai Shao, Nai-Yang Deng, Wei-Jie Chen, 2015, Inf. Sci..

An improved inexact Newton's method for unary optimization

Jianzhon Zhang, N. Deng, Zhaozhi Wang, 2001 .

Can Newton method be surpassed

N. Deng, Zhaozhi Wang, 1999 .

Combined outputs framework for twin support vector machines

N. Deng, Y. Shao, Xiang-Yu Hua, 2015, Applied Intelligence.

Leave-one-out Bounds for Support Vector Regression

Yingjie Tian, Naiyang Deng, Ying-jie Tian, 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

A New Algorithm for Classification Problems

Ionel M. Navon, N. Deng, Jing Chen, 2006 .

Unsupervised and Semi-Supervised Two-class Support Vector Machines

Yingjie Tian, Naiyang Deng, Ying-jie Tian, 2006, ICDM Workshops.

Biased p-norm support vector machine for PU learning

Zhiqiang Zhang, Ting Ke, Naiyang Deng, 2014, Neurocomputing.

Unsupervised and Semi-supervised Lagrangian Support Vector Machines with Polyhedral Perturbations

Kun Zhao, Yingjie Tian, Naiyang Deng, 2007, 2009 Third International Symposium on Intelligent Information Technology Application.

A new support vector machine for the classification of positive and unlabeled examples

Ling Zhen, Nai-Yang Deng, Chunhua Zhang, 2013 .

Robust Unsupervised and Semisupervised Bounded C-Support Vector Machines

Takashi Washio, Kun Zhao, Hiroshi Kuwajima, 2007, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007).