most citedExploring Algorithmic Fairness in Robust Graph Covering Problems

33 citations · 49 across the 4 of their papers we have counts for

collaborators

5 papers

math.OC20201 cited

ROC++: Robust Optimization in C++

Phebe Vayanos, Qing Jin, George Elissaios

Robust optimization is a very popular means to address decision-making problems affected by uncertainty. Its success has been fueled by its attractive robustness and scalability pr…

math.OC202033 cited

Exploring Algorithmic Fairness in Robust Graph Covering Problems

Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti +4

Fueled by algorithmic advances, AI algorithms are increasingly being deployed in settings subject to unanticipated challenges with complex social effects. Motivated by real-world d…

stat.ML2020

Learning Optimal Classification Trees: Strong Max-Flow Formulations

Sina Aghaei, Andres Gomez, Phebe Vayanos

We consider the problem of learning optimal binary classification trees. Literature on the topic has burgeoned in recent years, motivated both by the empirical suboptimality of heu…

cs.LG201912 cited

Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making

Sina Aghaei, Mohammad Javad Azizi, Phebe Vayanos

In recent years, automated data-driven decision-making systems have enjoyed a tremendous success in a variety of fields (e.g., to make product recommendations, or to guide the prod…

cs.SI20193 cited

Social Network Based Substance Abuse Prevention via Network Modification (A Preliminary Study)

Aida Rahmattalabi, Anamika Barman Adhikari, Phebe Vayanos +3

Substance use and abuse is a significant public health problem in the United States. Group-based intervention programs offer a promising means of preventing and reducing substance…