Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering 2015
DOI: 10.2991/eame-15.2015.178
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Implementation of Infeasible Kernel-Based Interior-Point Methods for Linearly Constrained Convex Optimization

Liqun Wu1,
K. Li2,
X.D. Wang3
et al.

Abstract: In this paper, we present the implementation of infeasible kernel-based primal-dual interior-point methods for linearly constrained convex optimization. Numerical results are provided to demonstrate the efficiency of the algorithms.

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