2 citations · 2 across the 3 of their papers we have counts for
5 papers
Performative Prediction with Selective Labels
Giovani Valdrighi, Isabel Valera, Marcos Medeiros Raimundo
Many social applications of machine learning exhibit performative effects: population behavior changes in response to deployed models. Performative prediction studies this interact…
PCE: Model-Agnostic Plausible Pareto-Optimal Counterfactual Explanations
Arthur Hendricks Mendes de Oliveira, Giovani Valdrighi, Marcos Medeiros Raimundo
The increasing use of machine learning algorithms in social applications has raised concerns about fairness and transparency, leading to the development of counterfactual explanati…
Long-term Fairness with Selective Labels
Giovani Valdrighi, Isabel Valera, Marcos Medeiros Raimundo
Long-term fairness algorithms aim to satisfy fairness beyond static and short-term notions by accounting for the dynamics between decision-making policies and population behavior.…
MFGB: A Min-Max Gradient Boosting Framework for Subgroup Fairness
Jansen S. B. Pereira, Giovani Valdrighi, Marcos Medeiros Raimundo
In recent years, fairness in machine learning has emerged as a critical concern to ensure that developed and deployed predictive models do not have disadvantageous predictions for…
Best Practices for Responsible Machine Learning in Credit Scoring
Giovani Valdrighi, Athyrson M. Ribeiro, Jansen S. B. Pereira +8
The widespread use of machine learning in credit scoring has brought significant advancements in risk assessment and decision-making. However, it has also raised concerns about pot…