Double data piling: a high-dimensional solution for asymptotically perfect multi-category classification

Cites Work

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Distance-Weighted Discrimination
Boundary behavior in high dimension, low sample size asymptotics of PCA
PCA consistency in high dimension, low sample size context
Continuum directions for supervised dimension reduction
Sparse HDLSS discrimination with constrained data piling
On the distribution of the largest eigenvalue in principal components analysis
Asymptotics of empirical eigenstructure for high dimensional spiked covariance
Subspace rotations for high-dimensional outlier detection
Double data piling leads to perfect classification
Surprises in high-dimensional ridgeless least squares interpolation
A General Framework For Consistency of Principal Component Analysis
On Strong Mixing Conditions for Stationary Gaussian Processes
Two Models of Double Descent for Weak Features
Distance-based outlier detection for high dimension, low sample size data
On the proliferation of support vectors in high dimensions*
Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting, and Regularization
Adjusting systematic bias in high dimensional principal component scores
The Generalization Error of Random Features Regression: Precise Asymptotics and the Double Descent Curve
Benign overfitting in linear regression
Reconciling modern machine-learning practice and the classical bias–variance trade-off
Weighted Distance Weighted Discrimination and Its Asymptotic Properties
The maximal data piling direction for discrimination
Geometric Representation of High Dimension, Low Sample Size Data
OUP accepted manuscript
The high-dimension, low-sample-size geometric representation holds under mild conditions
Achieving near Perfect Classification for Functional Data
Deep learning: a statistical viewpoint
Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation
Clustering high dimension, low sample size data using the maximal data piling distance
Optimal Linear Discriminant Analysis for High-Dimensional Functional Data

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