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Landslide is a common failure mode for levee, and the safety of which is always assessed by the value of safety factor. However, the safety assessment using the index of safety factor is usually unreasonable due to the uncertainty of soil characteristics, in contrast, the risk analysis by consideration of such uncertainties is more reasonable. Therefore, in the paper, the risk probability of levee...
The performance of popular and classical k-nearest neighbor classifier depends on the distance metric. Large margin nearest neighbor classifier using gradient optimization method is prone to local minima. In this paper, we present a Mahalanobis metric learning method based on cutting plane algorithm which reduces largely constraints for solving the semidefinite programming problem. Experimental results...
Nonparametric diffusion mixing estimator (DME) based blind signal separation (BSS) algorithm is proposed under the framework of natural gradient optimization method. In order to improve the performance of signal separation by BSS, the probability distributions of source signals must be described as accurately as possible. In this paper, we use the new data-driven bandwidth selection method based MDE...
First order optimization methods, while being powerful and rapidly convergent, suffer from the fact that as the descriptive geometric parameters change from iteration to iteration, corresponding to these new geometries, new meshes need to be implemented. Correspondingly the new topologies of the meshes introduce non-physical jumps in the object function. These jumps are seen as physical minima by...
Generalized cross entropy estimator (GCEE) based nonparametric Blind Signal Separation (BSS) algorithm is proposed under the framework of natural gradient optimization method. In order to improve the performance of signal separation by BSS, the probability distribution of source signals must be described as accurately as possible. Compared to the nonparametric fixed-width kernel density estimator...
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