Introduces a multi-resolution spatial partitioning and scan statistic method to detect unfairness in predictive models based on movement patterns, validated as effective on synthetic datasets.
arXiv preprint arXiv:2403.14040 , year=
2 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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cs.LG 2years
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Benchmark finds location encoders recover primary spatial coefficients consistently but secondary ones vary by scale, with raw-coordinate baseline competitive throughout.
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Assessing Predictive Models for Fairness Based on Movement Patterns
Introduces a multi-resolution spatial partitioning and scan statistic method to detect unfairness in predictive models based on movement patterns, validated as effective on synthetic datasets.
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Do Location Encoders Capture Spatial Effects? A GeoShapley Benchmark Across Scales
Benchmark finds location encoders recover primary spatial coefficients consistently but secondary ones vary by scale, with raw-coordinate baseline competitive throughout.