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Found 4 papers, 0 papers with code
A Deep Graph Neural Networks Architecture Design: From Global Pyramid-like Shrinkage Skeleton to Local Link Rewiring
Expressivity plays a fundamental role in evaluating deep neural networks, and it is closely related to understanding the limit of performance improvement.
Covariance Estimation for Matrix-valued Data
Covariance estimation for matrix-valued data has received an increasing interest in applications.
Matrix Linear Discriminant Analysis
We propose a novel linear discriminant analysis approach for the classification of high-dimensional matrix-valued data that commonly arises from imaging studies.
Elliptical modeling and pattern analysis for perturbation models and classfication
In this paper, we proposed a nonlinear parametric perturbation model that transforms the input feature patterns to a set of elliptical patterns, and studied the performance degradation issues associated with random forest classification technique using both the input and transform domain features.
