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Found 4 papers, 3 papers with code
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias
Large language models (LLMs) are increasingly essential in processing natural languages, yet their application is frequently compromised by biases and inaccuracies originating in their training data.
Inexact Simplification of Symbolic Regression Expressions with Locality-sensitive Hashing
Symbolic regression (SR) searches for parametric models that accurately fit a dataset, prioritizing simplicity and interpretability.
Minimum variance threshold for epsilon-lexicase selection
Parent selection plays an important role in evolutionary algorithms, and many strategies exist to select the parent pool before breeding the next generation.
Optimizing fairness tradeoffs in machine learning with multiobjective meta-models
We present a flexible framework for defining the fair machine learning task as a weighted classification problem with multiple cost functions.
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