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Pedro Saleiro

Aequitas Flow: Streamlining Fair ML Experimentation

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May 09, 2024
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Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraints

Mar 21, 2024
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DiConStruct: Causal Concept-based Explanations through Black-Box Distillation

Jan 26, 2024
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FiFAR: A Fraud Detection Dataset for Learning to Defer

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Dec 20, 2023
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Fairness-Aware Data Valuation for Supervised Learning

Mar 29, 2023
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A Case Study on Designing Evaluations of ML Explanations with Simulated User Studies

Feb 15, 2023
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Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation

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Nov 28, 2022
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LaundroGraph: Self-Supervised Graph Representation Learning for Anti-Money Laundering

Oct 25, 2022
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FairGBM: Gradient Boosting with Fairness Constraints

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Sep 19, 2022
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Understanding Unfairness in Fraud Detection through Model and Data Bias Interactions

Jul 13, 2022
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