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cs.LG2026
Causal Manifold Fairness: Enforcing Geometric Invariance in Representation Learning
Vidhi Rathore
Fairness in machine learning is increasingly critical, yet standard approaches often treat data as static points in a high-dimensional space, ignoring the underlying generative str…
cs.LG2025
Achieving Fair PCA Using Joint Eigenvalue Decomposition
Vidhi Rathore, Naresh Manwani
Principal Component Analysis (PCA) is a widely used method for dimensionality reduction, but it often overlooks fairness, especially when working with data that includes demographi…