@article {DBLP:journals/oms/Vieira12,
	title = {Interior-point methods based on kernel functions for symmetric optimization},
	journal = {Optimization Methods and Software},
	volume = {27},
	number = {3},
	year = {2012},
	note = {<p>n/a</p>
},
	pages = {513-537},
	abstract = {<p>We present a generalization to symmetric optimization of interior-point methods for linear optimization based on kernel functions. Symmetric optimization covers the three most common conic optimization problems: linear, second-order cone and semi-definite optimization problems. Namely, we adapt the interior-point algorithm described in Peng et al. [Self-regularity: A New Paradigm for Primal{\textendash}Dual Interior-point Algorithms. Princeton University Press, Princeton, NJ, 2002.] for linear optimization to symmetric optimization. The analysis is performed through Euclidean Jordan algebraic tools and a complexity bound is derived.</p>
},
	author = {Manuel V. C. Vieira}
}
