Sufficient dimension reduction via distance covariance with multivariate responses
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Nonparametric Statistics"
DOI: 10.1080/10485252.2018.1562065
Abstract: ABSTRACT In this article, we propose a new method for sufficient dimension reduction when both response and predictor are vectors. The new method, using distance covariance, keeps the model-free advantage, and can fully recover the… read more here.
Keywords: dimension reduction; distance covariance; sufficient dimension;
Hyperspectral Image Few-Shot Classification Network With Brownian Distance Covariance
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2023.3276972
Abstract: At present, how to achieve high-precision hyperspectral image classification (HSIC) under the condition of few samples is a hot research issue. Metric-based meta-learning methods have proved to be very successful in this field. However, in… read more here.
Keywords: classification; distance covariance; brownian distance; hyperspectral image ... See more keywords
Adaptive Mask Sampling and Manifold to Euclidean Subspace Learning With Distance Covariance Representation for Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3265388
Abstract: For the abundant spectral and spatial information recorded in hyperspectral images (HSIs), fully exploring spectral–spatial relationships has attracted widespread attention in the HSI classification (HSIC) community. However, there are still some intractable obstructs. For one… read more here.
Keywords: spectral spatial; distance covariance; adaptive mask;
Estimating Feature-Label Dependence Using Gini Distance Statistics
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2019.2960358
Abstract: Identifying statistical dependence between the features and the label is a fundamental problem in supervised learning. This paper presents a framework for estimating dependence between numerical features and a categorical label using generalized Gini distance,… read more here.
Keywords: distance statistics; distance; gini distance; dependence ... See more keywords
An omnibus approach to assess covariate balance in observational studies using the distance covariance
Sign Up to like & getrecommendations! Published in 2019 at "Statistical Methods in Medical Research"
DOI: 10.1177/0962280219878215
Abstract: Adequate baseline covariate balance among groups is critical in observational studies designed to estimate causal effects. Propensity score-based methods are popular ways to achieve covariate balance among groups. Existing methods are not easily generalizable to… read more here.
Keywords: distance covariance; covariate balance; covariate; observational studies ... See more keywords
Distance covariance for discretized stochastic processes
Sign Up to like & getrecommendations! Published in 2020 at "Bernoulli"
DOI: 10.3150/20-bej1206
Abstract: Given an iid sequence of pairs of stochastic processes on the unit interval we construct a measure of independence for the components of the pairs. We define distance covariance and distance correlation based on approximations… read more here.
Keywords: stochastic processes; distance; component processes; covariance discretized ... See more keywords