One Mirror Descent Algorithm for Convex Constrained Optimization Problems with non-standard growth properties

Polyak, B.: A general method of solving extremum problems. Soviet Mathematics Doklady. 8(3), 593–597 (1967), (in Russian)

1967

Earlier work this paper cites.

Shor, N. Z.: Generalized gradient descent with application to block programming. Kibernetika. 3(3), 53–55 (1967), (in Russian)

1967

Earlier work this paper cites.

Nemirovskii, A.: Efficient methods for large-scale convex optimization problems. Ekonomika i Matematicheskie Metody (1979), (in Russian)

1979

Earlier work this paper cites.

Nemirovsky, A., Yudin, D.: Problem Complexity and Method Efficiency in Optimization. J. Wiley & Sons, New York (1983)

1983

Earlier work this paper cites.

Nesterov, Y.: A method of solving a convex programming problem with convergence rate O ⁡ ( 1 / k 2 ) O(1/k^{2}) . Soviet Mathematics Doklady. 27(2), 372–376 (1983)

1983

Earlier work this paper cites.

Nemirovskii, A., Nesterov, Y.: Optimal methods of smooth convex minimization. USSR Computational Mathematics and Mathematical Physics. 25(2), 21–30, (1985), (in Russian)

1985

Earlier work this paper cites.

Ben-Tal, A., Nemirovski, A.: Robust Truss Topology Design via semidefinite programming. SIAM Journal on Optimization. 7(4), 991–1016 (1997)

1997

Earlier work this paper cites.

Ben-Tal, A., Nemirovski, A.: Lectures on Modern Convex Optimization. Society for Industrial and Applied Mathematics, Philadelphia (2001)

2001

Cited alongside, same era.

Vasilyev, F.: Optimization Methods. Fizmatlit, Moscow (2002), (in Russian)

2002

Cited alongside, same era.

Beck, A., Teboulle, M.: Mirror descent and nonlinear projected subgradient methods for convex optimization. Oper. Res. Lett. 31(3), 167–175 (2003)

2003

Cited alongside, same era.

Boyd, S., Vandenberghe, L.: Convex Optimization. New York: Cambridge University Press (2004)

2004

Cited alongside, same era.

Nesterov, Y.: Introductory Lectures on Convex Optimization: a basic course. Kluwer Academic Publishers, Massachusetts (2004)

2004

Cited alongside, same era.

Juditsky, A., Nemirovski, A.: First order methods for non-smooth convex large-scale optimization. I: general purpose methods. Optimization for Machine Learning, S. Sra et al, Eds. Cambridge, MA: MIT Press, 121–184 (2012)

2012

Later among the works it cites.

Juditsky, A., Nesterov, Y.: Deterministic and stochastic primal-gual subgradient algorithms for uniformly convex minimization. Stochastic Systems. 4(1), 44–80 (2014)

2014

Later among the works it cites.

Shpirko, S., Nesterov Y.: Primal-dual subgradient methods for huge-scale linear conic problem. SIAM Journal on Optimization. 24 (3), 1444 – 1457 (2014)

2014

Later among the works it cites.

Bayandina, A., Dvurechensky, P., Gasnikov, A., Stonyakin, F., Titov, A.: Mirror descent and convex optimization problems with non-smooth inequality constraints. In: LCCC Focus Period on Large-Scale and Distributed Optimization. Sweden, Lund: Springer. (Accepted) (2017) https://arxiv.org/abs/1710.06612

Original

2017

Later among the works it cites.