8 citations · 18 across the 5 of their papers we have counts for
5 papers
Convergence rates of the stochastic alternating algorithm for bi-objective optimization
Suyun Liu, Luis Nunes Vicente
Stochastic alternating algorithms for bi-objective optimization are considered when optimizing two conflicting functions for which optimization steps have to be applied separately…
The Sharpe predictor for fairness in machine learning
Suyun Liu, Luis Nunes Vicente
In machine learning (ML) applications, unfair predictions may discriminate against a minority group. Most existing approaches for fair machine learning (FML) treat fairness as a co…
A Stochastic Alternating Balance -Means Algorithm for Fair Clustering
Suyun Liu, Luis Nunes Vicente
In the application of data clustering to human-centric decision-making systems, such as loan applications and advertisement recommendations, the clustering outcome might discrimina…
Accuracy and Fairness Trade-offs in Machine Learning: A Stochastic Multi-Objective Approach
Suyun Liu, Luis Nunes Vicente
In the application of machine learning to real-life decision-making systems, e.g., credit scoring and criminal justice, the prediction outcomes might discriminate against people wi…
The stochastic multi-gradient algorithm for multi-objective optimization and its application to supervised machine learning
Suyun Liu, Luis Nunes Vicente
Optimization of conflicting functions is of paramount importance in decision making, and real world applications frequently involve data that is uncertain or unknown, resulting in…