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Cited article:

A new primal-dual interior-point method for semidefinite optimization based on a parameterized kernel function

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Optimization and Engineering 22 (1) 293 (2021)
https://doi.org/10.1007/s11081-020-09516-9

Kernel-function-based primal-dual interior-point methods for convex quadratic optimization over symmetric cone

Xinzhong Cai, Lin Wu, Yujing Yue, Minmin Li and Guoqiang Wang
Journal of Inequalities and Applications 2014 (1) (2014)
https://doi.org/10.1186/1029-242X-2014-308

A Large-Update Feasible Interior-Point Algorithm for Convex Quadratic Semi-definite Optimization Based on a New Kernel Function

B. Kheirfam and F. Hasani
Journal of the Operations Research Society of China 1 (3) 359 (2013)
https://doi.org/10.1007/s40305-013-0023-x

Primal-dual interior-point algorithm for semidefinite optimization based on a new kernel function with trigonometric barrier term

Behrouz Kheirfam
Numerical Algorithms 61 (4) 659 (2012)
https://doi.org/10.1007/s11075-012-9557-y

Handbook on Semidefinite, Conic and Polynomial Optimization

Maziar Salahi and Tamás Terlaky
International Series in Operations Research & Management Science, Handbook on Semidefinite, Conic and Polynomial Optimization 166 437 (2012)
https://doi.org/10.1007/978-1-4614-0769-0_15

A unified kernel function approach to primal-dual interior-point algorithms for convex quadratic SDO

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Numerical Algorithms 57 (4) 537 (2011)
https://doi.org/10.1007/s11075-010-9444-3

Kernel-function Based Primal-Dual Algorithms forP*(κ) Linear Complementarity Problems

M. EL Ghami and T. Steihaug
RAIRO - Operations Research 44 (3) 185 (2010)
https://doi.org/10.1051/ro/2010014