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Cheriton School of Computer Science, University of Waterloo
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Achieving fairness in machine learning may come at a lower data cost than previously thought, as this framework balances bias mitigation with representation needs.
Forget sifting through verbose model descriptions – this search framework uses structured tables to surface task-aligned yet measurably different models, helping you find the *right* model, faster.