We apply Stochastic Meta-Descent (SMD), a stochastic gradient optimization method with gain vector adaptation, to the training of Conditional Random Fields (CRFs). On several larg...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark ...
— In this paper we present a gradient method to iteratively update local controllers of a distributed linear system driven by stochastic disturbances. The control objective is to...
In this paper we consider the problem of computing the area-based affine distance for a convex domain in the plane. Since this affine distance satisfies a non-homogeneous Monge-Amp...
Moacyr A. H. B. da Silva, Ralph Teixeira, Sin&eacu...
A new algorithm for solving smooth large-scale minimization problems with bound constraints is introduced. The way of dealing with active constraints is similar to the one used in...
In this paper two classes of iterative methods for saddle point problems are considered: inexact Uzawa algorithms and a class of methods with symmetric preconditioners. In both cas...