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Found 4 papers, 0 papers with code
A Flexible Framework for Nonparametric Graphical Modeling that Accommodates Machine Learning
In addition, we show that for 2 of these measures there are simple, strong plug-in estimators that require only the estimation of a conditional mean.
A Kernel-based Test of Independence for Cluster-correlated Data
The Hilbert-Schmidt Independence Criterion (HSIC) is a powerful kernel-based statistic for assessing the generalized dependence between two multivariate variables.
On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure
Originally developed for imputing missing entries in low rank, or approximately low rank matrices, matrix completion has proven widely effective in many problems where there is no reason to assume low-dimensional linear structure in the underlying matrix, as would be imposed by rank constraints.
Statistical Inference Using Mean Shift Denoising
In this paper, we study how the mean shift algorithm can be used to denoise a dataset.
