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» Gradient Convergence in Gradient methods with Errors
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JSCIC
2010
97views more  JSCIC 2010»
13 years 2 months ago
Finite Element Characteristic Methods Requiring no Quadrature
The characteristic methods are known to be very efficient for convection-diffusion problems including the Navier-Stokes equations. Convergence is established when the integrals ar...
Olivier Pironneau
NA
2010
69views more  NA 2010»
13 years 5 months ago
Partial spectral projected gradient method with active-set strategy for linearly constrained optimization
A method for linearly constrained optimization which modifies and generalizes recent box-constraint optimization algorithms is introduced. The new algorithm is based on a relaxed...
Marina Andretta, Ernesto G. Birgin, José Ma...
AAAI
2011
12 years 7 months ago
Differential Eligibility Vectors for Advantage Updating and Gradient Methods
In this paper we propose differential eligibility vectors (DEV) for temporal-difference (TD) learning, a new class of eligibility vectors designed to bring out the contribution of...
Francisco S. Melo
ICIP
2004
IEEE
14 years 9 months ago
A gradient based approach for stereoscopic error concealment
Error concealment is an important field of research in image processing. Many methods were applied to conceal block losses in monocular images. In this paper we present a concealm...
Matthias Kunter, Sebastian Knorr, Carsten Clemens,...
ECML
2005
Springer
14 years 1 months ago
Combining Bias and Variance Reduction Techniques for Regression Trees
Gradient Boosting and bagging applied to regressors can reduce the error due to bias and variance respectively. Alternatively, Stochastic Gradient Boosting (SGB) and Iterated Baggi...
Yuk Lai Suen, Prem Melville, Raymond J. Mooney