摘要: This paper presents two reformulations of the dual constrained least-squares problem over convex cones. In addition, it extends Nesterov's excessive gap method 1 [Excessive technique in nonsmooth minimization, SIAM J. Optim. 161 2005, pp. 235–249 electronic] to more general problems. The conic is then solved by applying resulting modified method, or smooth [Smooth minimization non-smooth functions, Math. Program. 1031, Ser. A 127–152], 2 electronic], reformulations. Numerical experiments show that this approach obtains relatively accurate solutions for large-scale problems using less CPU time than interior-point method-based state-of-art software do and these on instances possibly with degeneracy [F. Alizadeh, J.-P.A. Haeberly, M.L. Overton, Complementarity nondegeneracy semidefinite programming, 772, B 1997, 111–128]. easily related quadratic programs.
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