Latest Articles for Outliers

A look into Hyperplane Distance Depth and its role in measuring centrality.

ASER offers a way to enhance quantized language models without losing performance.

Robust Bayesian methods improve data analysis in astronomy, addressing outliers effectively.

Machine learning aids astronomers in studying the Cosmic Microwave Background.

Learn how ShiftQuant and L1 normalization improve neural network efficiency.

Learn how to identify and address prediction errors in machine learning.

Learn how Wasserstein Spatial Depth helps make sense of complex data.

Learn how partial Gini covariance improves analysis of high-dimensional, heavy-tailed data.

Learn about adversarial and heavy-tailed outliers in data analysis.

A new method for better data sorting and classification.

Learn how researchers tackle outliers to improve data accuracy.

Discover how robust regression enhances data analysis for better predictions.

New method enhances oil-flow analysis using neural networks for better flow predictions.

Research finds ways to reduce AI model size while maintaining accuracy.

A look at improving treatment effect analysis using tail-trimming techniques.

A new algorithm improves clustering fairness by removing outliers.

Improving Gromov-Wasserstein distance to handle outliers effectively in diverse data sets.

Revolutionizing point cloud completion using Hyperbolic Chamfer Distance.

Improving location accuracy using wireless signals in complex environments.

Learn how RDPCA improves the analysis of density data amidst outliers.