Explainable AI via learning to optimize.
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ABSTRACT:
SUBMITTER: Heaton H
PROVIDER: S-EPMC10284861 | biostudies-literature | 2023 Jun
REPOSITORIES: biostudies-literature
Publications
Explainable AI via learning to optimize.
Heaton Howard H Fung Samy Wu SW
Scientific reports 20230621 1
Indecipherable black boxes are common in machine learning (ML), but applications increasingly require explainable artificial intelligence (XAI). The core of XAI is to establish transparent and interpretable data-driven algorithms. This work provides concrete tools for XAI in situations where prior knowledge must be encoded and untrustworthy inferences flagged. We use the "learn to optimize" (L2O) methodology wherein each inference solves a data-driven optimization problem. Our L2O models are str ...[more]
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