Sina Aghaei

According to our database, Sina Aghaei authored at least 9 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Learning Optimal Classification Trees Robust to Distribution Shifts.

Nathan Justin, Sina Aghaei, Andrés Gómez, Phebe Vayanos

CoRR, 2023

ODTlearn: A Package for Learning Optimal Decision Trees for Prediction and Prescription.

Patrick Vossler, Sina Aghaei, Nathan Justin, Nathanael Jo, Andrés Gómez, Phebe Vayanos

CoRR, 2023

Learning Optimal Fair Decision Trees: Trade-offs Between Interpretability, Fairness, and Accuracy.

Nathanael Jo, Sina Aghaei, Jack Benson, Andrés Gómez, Phebe Vayanos

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

Fairness in Contextual Resource Allocation Systems: Metrics and Incompatibility Results.

Nathanael Jo, Bill Tang, Kathryn Dullerud, Sina Aghaei, Eric Rice, Phebe Vayanos

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Learning Optimal Fair Classification Trees.

Nathanael Jo, Sina Aghaei, Jack Benson, Andrés Gómez, Phebe Vayanos

CoRR, 2022

2021

Learning Optimal Prescriptive Trees from Observational Data.

Nathanael Jo, Sina Aghaei, Andrés Gómez, Phebe Vayanos

CoRR, 2021

Strong Optimal Classification Trees.

Sina Aghaei, Andrés Gómez, Phebe Vayanos

CoRR, 2021

2020

Learning Optimal Classification Trees: Strong Max-Flow Formulations.

Sina Aghaei, Andrés Gómez, Phebe Vayanos

CoRR, 2020

2019

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

Sina Aghaei, Mohammad Javad Azizi, Phebe Vayanos

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019