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cs.LG2023
SORTAD: Self-Supervised Optimized Random Transformations for Anomaly Detection in Tabular Data
Guy Hay, Pablo Liberman
We consider a self-supervised approach to anomaly detection in tabular data. Random transformations are applied to the data, and then each transformation is identified based on its…
cs.LG2023
Marginal Laplacian Score
Guy Hay, Ohad Volk
High-dimensional imbalanced data poses a machine learning challenge. In the absence of sufficient or high-quality labels, unsupervised feature selection methods are crucial for the…