User menu

Smoothing Technique and its Applications in Semidefinite Optimization

Bibliographic reference Nesterov, Yurii. Smoothing Technique and its Applications in Semidefinite Optimization. In: Mathematical Programming, Vol. 110, no. 2, p. 245-259 (Juillet 2007)
Permanent URL
  1. Helmberg, C., Rendl, F. A spectral bundle method for semidenite programming. In: Technical Report SC 97-37, Konrad-Zuse-Zentrum fur Informationstechnik Berlin 1997
  2. Helmberg, C., Oustry, F. Bundle methods to minimize the maximum eigenvalue function. In: Vandenberghe, R. Saigal, H. Wolkovicz, (eds.) Hanbook on semidefinite programming. Theory, algorithms and applications. Kluwer Dordrecht 1999
  3. Lemarechal, C., Oustry, F. Nonsmooth algorithms to solve semidefinite programs. In: El Ghaoui, L. Niculescu S.I. (eds.) Recent advances on LMI methods in control. Advances in design and control series. SIAM 1999
  4. Lewis Adrian S., Sendov Hristo S., Twice Differentiable Spectral Functions, 10.1137/s089547980036838x
  5. Nayakkankuppam, M.V., Tymofejev, Y. A parallel implementation of the spectral bundle method for large-scale semidefinite programs. In: Proceedings of the 8th SIAM conference on applied linear algebra, Williamsburg (VA) 2003
  6. Nemirovskii A.S., Yudin D.B. (1983) Problem complexity and method efficiency in optimization. Wiley, New York
  7. Nesterov Yurii, Introductory Lectures on Convex Optimization, ISBN:9781461346913, 10.1007/978-1-4419-8853-9
  8. Nesterov Yu. (2005) Smooth minimization of non-smooth functions. Mathematical programming, 103(1): 127–152
  9. Nesterov Yu. (2005) Excessive gap technique in nonsmooth convex minimization. SIAM J Optim 16(1): 235–249
  10. Nesterov, Yu. Unconstrained convex minimization in relative scale. CORE Discussion Paper 2003/96 (2003)