Mirror descent and nonlinear projected subgradient methods for convex optimization

[1]  Arkadi Nemirovski,et al.  The Ordered Subsets Mirror Descent Optimization Method with Applications to Tomography , 2001, SIAM J. Optim..

[2]  D. Bertsekas,et al.  Incremental subgradient methods for nondifferentiable optimization , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[3]  Marc Teboulle,et al.  An Interior Proximal Algorithm and the Exponential Multiplier Method for Semidefinite Programming , 1998, SIAM J. Optim..

[4]  K. Kiwiel Proximal Minimization Methods with Generalized Bregman Functions , 1997 .

[5]  Marc Teboulle,et al.  Convergence Analysis of a Proximal-Like Minimization Algorithm Using Bregman Functions , 1993, SIAM J. Optim..

[6]  Marc Teboulle,et al.  Entropic Proximal Mappings with Applications to Nonlinear Programming , 1992, Math. Oper. Res..

[7]  Jerzy Seidler,et al.  Problem Complexity and Method Efficiency in Optimization , 1984 .

[8]  John Darzentas,et al.  Problem Complexity and Method Efficiency in Optimization , 1983 .

[9]  Y. Censor,et al.  An iterative row-action method for interval convex programming , 1981 .

[10]  R. Rockafellar Monotone Operators and the Proximal Point Algorithm , 1976 .

[11]  J. Kemperman,et al.  On the Optimum Rate of Transmitting Information , 1969 .

[12]  L. Bregman The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming , 1967 .

[13]  K. Schittkowski,et al.  NONLINEAR PROGRAMMING , 2022 .