A 14-code content model for local post-hoc AI explanations, derived from 325 user statements and validated by experts with high reliability scores.
Privacy- preserving record linkage using Bloom filters: A systematic literature review,
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Bloom filter encodings convert data samples to bit arrays that support comparable classifier performance to raw data across text, time-series, tabular, and image datasets while delivering consistent memory savings.
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What Should Explanations Contain? A Human-Centered Explanation Content Model for Local, Post-Hoc Explanations
A 14-code content model for local post-hoc AI explanations, derived from 325 user statements and validated by experts with high reliability scores.
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Bloom Filter Encoding for Machine Learning
Bloom filter encodings convert data samples to bit arrays that support comparable classifier performance to raw data across text, time-series, tabular, and image datasets while delivering consistent memory savings.