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Codebase for SEFS: Self-Supervision Enhanced Feature Selection with Correlated Gates

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Codebased for SEFS

SEFS: Self-Supervision Enhanced Feature Selection with Correlated Gates

Authors: Changhee Lee*, Fergus Imrie*, Mihaela van der Schaar

Reference: Changhee Lee, Fergus Imrie, Mihaela van der Schaar, "Self-Supervised Enhanced Feature Selection with Correlated Gates," International Conference on Learning Representations (ICLR), 2022.

Paper Link: https://openreview.net/forum?id=oDFvtxzPOx

Contact: [email protected]

This directory contains implementations of SEFS for feature selection (and variable importance) using one synthetic (Block-Structured Noisy Two-Moons) dataset.

To run the SEFS see jupyter-notebook tutorial of SEFS in tutorial.ipynb.

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