http://orcid.org/0000-0002-4469-314X
References
- Bertsekas DP. Incremental gradient, subgradient, and proximal methods for convex optimization: a survey. In: Sra S, Nowozin S, Wright SJ, editors. Optimization for machine learning, Neural Information Processing Series. Cambridge (MA): MIT Press; 2012. p. 85–120.
- Nedic A, Bertsekas DP. Incremental subgradient methods for nondifferentiable optimization. SIAM J Optim. 2001;12(1):109–138. doi: 10.1137/S1052623499362111
- Ben-Tal A, Margalit T, Nemirovski A. The ordered subsets mirror descent optimization method with applications to tomography. SIAM J Optim. 2001;12(1):79–108. doi: 10.1137/S1052623499354564
- Xiao L. Dual averaging methods for regularized stochastic learning and online optimization. J Mach Learn Res. 2010;11:2543–2596.
- Gurbuzbalaban M, Ozdaglar A, Parrilo PA. On the convergence rate of incremental aggregated gradient algorithms. SIAM J Optim. 2017;27(2):1035–1048. doi: 10.1137/15M1049695
- Wei Z, He QH. Nonsmooth steepest descent method by proximal subdifferentials in Hilbert spaces. J Optim Theory Appl. 2014;161(2):465–477. doi: 10.1007/s10957-013-0444-z
- Bauschke HH, Bolte J, Teboulle M. A descent lemma beyond Lipschitz gradient continuity: first-order methods revisited and applications. Math Oper Res. 2017;42(2):330–348. doi: 10.1287/moor.2016.0817
- Beck A, Teboulle M. Mirror descent and nonlinear projected subgradient methods for convex optimization. Oper Res Lett. 2003;31(3):167–175. doi: 10.1016/S0167-6377(02)00231-6
- Nemirovskii AS, Yudin DB. Problem complexity and method efficiency in optimization. Hoboken (NJ): Wiley; 1983.
- Nesterov Y. Primal-dual subgradient methods for convex problems. Math Program. 2009;120(1):221–259. doi: 10.1007/s10107-007-0149-x
- Zhou Z, Mertikopoulos P, Bambos N, et al. Mirror descent in non-convex stochastic programming. arXiv:1706.05681, 2017.
- Shalev-Shwartz S. Online learning and online convex optimization. Found Trends Mach Learn. 2012;4(2):107–194. doi: 10.1561/2200000018
- Bolte J, Teboulle M. Barrier operators and associated gradient-like dynamical systems for constrained minimization problems. SIAM J Control Optim. 2003;42(4):1266–1292. doi: 10.1137/S0363012902410861
- Combettes PL, Pesquet J-C. Stochastic quasi-Fejér block-coordinate fixed point iterations with random sweeping. SIAM J Optim. 2015;25(2):1221–1248. doi: 10.1137/140971233
- Cruz JYB. On proximal subgradient splitting method for minimizing the sum of two nonsmooth convex functions. Set-Valued Var Anal. 2017;25(2):245–263. doi: 10.1007/s11228-016-0376-5