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JMLR
2006
97views more  JMLR 2006»
13 years 9 months ago
Learning Coordinate Covariances via Gradients
We introduce an algorithm that learns gradients from samples in the supervised learning framework. An error analysis is given for the convergence of the gradient estimated by the ...
Sayan Mukherjee, Ding-Xuan Zhou
CVPR
2007
IEEE
14 years 12 months ago
Gradient Intensity: A New Mutual Information-Based Registration Method
Conventional mutual information (MI)-based registration using pixel intensities is time-consuming and ignores spatial information, which can lead to misalignment. We propose a met...
Ramtin Shams, Parastoo Sadeghi, Rodney A. Kennedy
SIAMMAX
2010
145views more  SIAMMAX 2010»
13 years 4 months ago
Adaptive First-Order Methods for General Sparse Inverse Covariance Selection
In this paper, we consider estimating sparse inverse covariance of a Gaussian graphical model whose conditional independence is assumed to be partially known. Similarly as in [5],...
Zhaosong Lu
CSSE
2008
IEEE
14 years 4 months ago
Stochastic Gradient Algorithm for Multi-input Systems Based on the Auxiliary Model
—This paper presents an auxiliary model based stochastic gradient parameter estimation algorithm for multiinput output-error systems by minimizing a quadratic cost function. The ...
Yuwu Liao, Xianfang Wang, Rui Feng Ding
SAC
2009
ACM
14 years 4 months ago
A gradient oriented recombination scheme for evolution strategies
This paper proposes a novel recombination scheme for evolutionary algorithms, which can guide the new population generation towards the maximum increase of the objective function....
Haifeng Chen, Guofei Jiang