Hinder, O., Sidford, A., Sohoni, N.: Near-optimal methods for minimizing star-convex functions and beyond. In: Conference on Learning Theory, pp. 1894–1938. PMLR (2020) Hu, B., Seiler, P., Lessard, L.: Analysis of biased stochastic gradient descent using sequential semidefinite program...
The possible employment of gradient methods for solving this problem is investigated.doi:10.1016/0041-5553(71)90144-3Ya. I. Al'berElsevier B.V.Ussr Computational Mathematics & Mathematical PhysicsAlber, Ya. I.: The problem of the minimization of smooth functionals by gradient methods, USSR ...
Polyak, B.T.: Gradient methods for minimizing functionals (in Russian). Z. Vychislitel’noı Mat. Matematicheskoı Fiziki 643–653 (1963) Robinson, S.M.: Some continuity properties of polyhedral multifunctions. Math. Oper. Res. 5, 206–214 (1980) Article Google Scholar Rockafellar,...
A.A Goldstein Minimizing functionals on Hilbert space Computer Methods in Optimization Problems, Academic Press, New York (1964), pp. 159-165 View PDFView articleGoogle Scholar 23. B.T Polyak Gradient methods for the minimization of functionals Zh. Vychisl. Mat. i Mat. Fiz., 3 (1963), pp...
Notes 1. We avoid here the distinction between minimizing movements and generalized minimizing movements, which is not crucial in our analysis. 2. Unfortunately, some knowledge of French is required (even if not forbidden, English is unusual in the Bourbaki seminar, since “Nicolas Bourbaki a une...
- International Conference on Scale Space & Variational Methods in Computer Vision 被引量: 194发表: 2011年 The parabolic-parabolic Keller-Segel system with critical diffusion as a gradient flow in $\\RR^d$, $d \\ge 3$ The solution is constructed by using a minimizing scheme involving the ...
Andra, "The topological gradient in anisotropic elasticity with an eye towards lightweight design," Mathematical Methods in the Applied Sciences, vol. 37, no. 11, pp. 1624-1641, Jul. 2014.M. Schneider, H. Andra, The topological gradient in anisotropic elasticity with an eye towards light...
Polyak, B.T.: Gradient methods for minimizing functionals. Zhur- nal Vychislitel'noi Matematiki i Matematicheskoi Fiziki 3(4), 643–653 (1963) 66. Haas, P.J., Koenig, C.: A bi-level Bernoulli scheme for database sampling. In: Proceedings of the ACM SIGMOD International Conference on...
Classical stochastic gradient methods are well suited for minimizing expected-value objective functions. However, they do not apply to the minimization of a nonlinear function involving expected values or a composition of two expected-value functions, i.e., the problem minxEv[fv(Ew[gw(x)])]. ...
approximation. In addition, one should mention the conditions– based on scaling properties – determined by Levy and co-workers for the exchange and correlation functionals. But as thingsstand, these functionals cannot lead to exact results as they do not satisfy the functionalN-representability ...