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SAILS

model1 events
papersTODAY 04:00 UTC

SAILS: New Method Reveals Functional Form of Feature Interactions in ML Models

A new arXiv paper introduces SAILS, a surrogate-based approach that uses local effect smooths to characterize how features interact inside machine learning models. Unlike prior explanation techniques that only flag or score interactions, or that handle just a narrow set of interaction shapes, SAILS aims to expose the actual functional form of those interactions. The work is posted as a cross-listing on arXiv's cs.AI and cs.LG categories.

interpretability/explainable-ai/research/arxiv