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» On the convergence of Hill's method
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ICML
2006
IEEE
16 years 1 months ago
Accelerated training of conditional random fields with stochastic gradient methods
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 ...
93
Voted
CDC
2009
IEEE
106views Control Systems» more  CDC 2009»
15 years 5 months ago
Gradient methods for iterative distributed control synthesis
— 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...
Karl Martensson, Anders Rantzer
112
Voted
JMIV
2008
268views more  JMIV 2008»
15 years 21 days ago
A Fast Marching Method for the Area Based Affine Distance
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...
ANOR
2002
100views more  ANOR 2002»
15 years 18 days ago
A Limited-Memory Multipoint Symmetric Secant Method for Bound Constrained Optimization
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...
Oleg P. Burdakov, José Mario Martíne...
118
Voted
MOC
2002
120views more  MOC 2002»
15 years 12 days ago
Analysis of iterative methods for saddle point problems: a unified approach
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...
Walter Zulehner