311 search results - page 1 / 63 » Gradient Convergence in Gradient methods with Errors |
SIAMJO
2000
13 years 4 months ago
2000
We consider the gradient method xt+1 = xt + t(st + wt), where st is a descent direction of a function f : n and wt is a deterministic or stochastic error. We assume that f is Lip...
CDC
2010
IEEE
13 years 1 days ago
2010
IEEE
The asymptotic behavior of stochastic gradient algorithms is studied. Relying on some results of differential geometry (Lojasiewicz gradient inequality), the almost sure pointconve...
MP
2010
13 years 3 months ago
2010
Convex optimization problems arising in applications, possibly as approximations of intractable problems, are often structured and large scale. When the data are noisy, it is of i...
SIAMIS
2011
12 years 12 months ago
2011
The convergence rate is analyzed for the sparse reconstruction by separable approximation (SpaRSA) algorithm for minimizing a sum f(x) + ψ(x), where f is smooth and ψ is convex, ...
AUTOMATICA
2006
13 years 5 months ago
2006
In this paper, the complex-step method is applied in the setting of numerical optimisation problems involving dynamical systems modelled as nonlinear differential equations. The m...