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AMC
2008
88views more  AMC 2008»
14 years 12 months ago
Global convergence of a modified spectral FR conjugate gradient method
Abstract: The nonlinear conjugate gradient method is widely used in unconstrained optimization. However, the line search is very difficult or expensive sometimes. In this paper, we...
Shou-qiang Du, Yuan-yuan Chen
TNN
1998
94views more  TNN 1998»
14 years 11 months ago
Global convergence of Oja's subspace algorithm for principal component extraction
—Oja’s principal subspace algorithm is a well-known and powerful technique for learning and tracking principal information in time series. A thorough investigation of the conve...
Tianping Chen, Yingbo Hua, Wei-Yong Yan
ORL
2008
115views more  ORL 2008»
14 years 11 months ago
On the convergence of stochastic dual dynamic programming and related methods
We discuss the almost-sure convergence of a broad class of sampling algorithms for multi-stage stochastic linear programs. We provide a convergence proof based on the finiteness o...
Andrew B. Philpott, Z. Guan
FOCM
2008
88views more  FOCM 2008»
14 years 10 months ago
Convergence of the Magnus Series
The Magnus series is an infinite series which arises in the study of linear ordinary differential equations. If the series converges, then the matrix exponential of the sum equals...
Per Christian Moan, Jitse Niesen
ICML
2003
IEEE
16 years 17 days ago
TD(0) Converges Provably Faster than the Residual Gradient Algorithm
In Reinforcement Learning (RL) there has been some experimental evidence that the residual gradient algorithm converges slower than the TD(0) algorithm. In this paper, we use the ...
Ralf Schoknecht, Artur Merke