Nai-Yang Deng merges Support vector machine with Structural risk minimization in his research. Nai-Yang Deng applies his multidisciplinary studies on Structural risk minimization and Support vector machine in his research. His study brings together the fields of Consistency (knowledge bases) and Artificial intelligence. His Pseudo amino acid composition research extends to the thematically linked field of Gene. His study in Dipeptide extends to Pseudo amino acid composition with its themes. His work often combines Dipeptide and Amino acid studies. Amino acid and Nucleic acid are two areas of study in which he engages in interdisciplinary research. He merges many fields, such as Nucleic acid and RNA, in his writings. He performs multidisciplinary study in RNA and RNA-binding protein in his work.
Artificial intelligence is frequently linked to Class (philosophy) in his study. Nai-Yang Deng combines Support vector machine and Relevance vector machine in his research. He incorporates Relevance vector machine and Structured support vector machine in his research. While working in this field, Nai-Yang Deng studies both Structured support vector machine and Support vector machine. Pattern recognition (psychology) is closely attributed to Artificial intelligence in his work. Machine learning and Computational Science and Engineering are frequently intertwined in his study. In most of his Computational Science and Engineering studies, his work intersects topics such as Machine learning. Nai-Yang Deng merges many fields, such as Algorithm and Operating system, in his writings. Borrowing concepts from Algorithm, he weaves in ideas under Operating system.
His Artificial intelligence research spans across into fields like Data mining and Computer vision. He connects Computer vision with Artificial intelligence in his research. His work in Linguistics is not limited to one particular discipline; it also encompasses Feature (linguistics). His study connects Linguistics and Feature (linguistics). In his research, Nai-Yang Deng undertakes multidisciplinary study on Extraction (chemistry) and Chromatography. Nai-Yang Deng undertakes multidisciplinary investigations into Chromatography and Extraction (chemistry) in his work. His Mechanical engineering study often links to related topics such as Manifold (fluid mechanics). His Manifold (fluid mechanics) study frequently draws connections between related disciplines such as Mechanical engineering. His study deals with a combination of Remote sensing and Hyperspectral imaging.
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Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions
Naiyang Deng;Yingjie Tian;Chunhua Zhang.
Improvements on Twin Support Vector Machines
Yuan-Hai Shao;Chun-Hua Zhang;Xiao-Bo Wang;Nai-Yang Deng.
IEEE Transactions on Neural Networks (2011)
iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins.
Yan Xu;Xiao-Jian Shao;Ling-Yun Wu;Nai-Yang Deng.
Nonmonotonic trust region algorithm
N. Y. Deng;Y. Xiao;F. J. Zhou.
Journal of Optimization Theory and Applications (1993)
iNitro-Tyr: prediction of nitrotyrosine sites in proteins with general pseudo amino acid composition.
Yan Xu;Xin Wen;Li-Shu Wen;Ling-Yun Wu.
PLOS ONE (2014)
New Quasi-Newton Equation and Related Methods for Unconstrained Optimization
J. Z. Zhang;N. Y. Deng;L. H. Chen.
Journal of Optimization Theory and Applications (1999)
An efficient weighted Lagrangian twin support vector machine for imbalanced data classification
Yuan-Hai Shao;Wei-Jie Chen;Jing-Jing Zhang;Zhen Wang.
Pattern Recognition (2014)
Nonparallel hyperplane support vector machine for binary classification problems
Yuan-Hai Shao;Wei-Jie Chen;Nai-Yang Deng.
Information Sciences (2014)
Least squares recursive projection twin support vector machine for classification
Yuan-Hai Shao;Nai-Yang Deng;Zhi-Min Yang.
Pattern Recognition (2012)
An ε-twin support vector machine for regression
Yuan-Hai Shao;Chun-Hua Zhang;Zhi-Min Yang;Ling Jing.
Neural Computing and Applications (2013)
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