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RISMultiplicative distance: a method to alleviate distance instability for high-dimensional data
Recently, it has been shown that under a broad set of conditions, the commonly used distance functions will become unstable in high-dimensional data space; i.e., the distance to the farthest data point approaches the distance to the nearest data...
Bayesian variable selection with shrinking and diffusing priors
Adaptive Lasso estimators for ultrahigh dimensional generalized linear models
Discernible visualization of high dimensional data using label information
the same origin at the center of the circle.We propose a novel method toward automatic axes adjustment for high dimensional data in Star Coordinate visualization method.This method finds the best 2-dimensional view point (discernible visualization...
Weighted Semi-Supervised Manifold Clustering via sparse representation
over the last few years, manifold clustering has attracted considerable interest in high-dimensional data clustering. However achieving accurate clustering results that match user desires and data structure is still an open problem. One way to do so...