Hong-Kun Xu is affiliated with Hangzhou Dianzi University in China and has an extensive research profile primarily in the fields of Mathematics and Computer Science. Their work spans several subfields, including Computational Theory and Mathematics, Numerical Analysis, Applied Mathematics, Geometry and Topology, and Mathematical Physics.
Their main research topics focus on Optimization and Variational Analysis, Advanced Optimization Algorithms Research, Fixed Point Theorems Analysis, Numerical methods in inverse problems, Sparse and Compressive Sensing Techniques, Nonlinear Differential Equations Analysis, and Nonlinear Partial Differential Equations.
Hong-Kun Xu has published numerous papers in a variety of scientific venues. Frequent publication platforms include Optimization, arXiv (Cornell University), Numerical Functional Analysis and Optimization, Carpathian Journal of Mathematics, and SIAM Journal on Optimization. The notable recent papers include:
Collaboration is an important aspect of Hong-Kun Xu's academic activities. Frequent co-authors include Vũ Thị Hương, Nguyen Dong Yen, Najla Altwaijry, Souhail Chebbi, and Tiexin Guo.
In addition to articles, Hong-Kun Xu has contributed to book publications, including a work published by Frontiers Media titled "2022 Applied Mathematics and Statistics - Editor's Pick" in 2023.
Hong-Kun Xu
Hong Kun Xu
Hong-Kun Xu
Kok-Keong Tan;Hong-Kun Xu
H K Xu
Giuseppe Marino;Hong-Kun Xu
Giuseppe Marino;Hong-Kun Xu
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Carlos Martinez-Yanes;Hong-Kun Xu
H. K. Xu;T. H. Kim
Hong-Kun Xu;Ramesh G. Ori
Hong-Kun Xu;Hong-Kun Xu
Tae-Hwa Kim;Hong-Kun Xu
Kok-Keong Tan;Hong Kun Xu
Genaro Lopez Acedo;Hong-Kun Xu
Teck-Cheong Lim;Hong-Kun Xu
Hong-Kun Xu
Fenghui Wang;Hong-Kun Xu;Hong-Kun Xu
Tae-Hwa Kim;Hong-Kun Xu
Hong-Kun Xu
Vittorio Colao;Giuseppe Marino;Hong-Kun Xu
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