1 citations · 1 across the 5 of their papers we have counts for
5 papers
Designing Ambiguity Sets for Distributionally Robust Optimization Using Structural Causal Optimal Transport
Ahmad-Reza Ehyaei, Golnoosh Farnadi, Samira Samadi
Distributionally robust optimization tackles out-of-sample issues like overfitting and distribution shifts by adopting an adversarial approach over a range of possible data distrib…
Wasserstein Distributionally Robust Optimization Through the Lens of Structural Causal Models and Individual Fairness
Ahmad-Reza Ehyaei, Golnoosh Farnadi, Samira Samadi
In recent years, Wasserstein Distributionally Robust Optimization (DRO) has garnered substantial interest for its efficacy in data-driven decision-making under distributional uncer…
From Fragile to Certified: Wasserstein Audits of Group Fairness Under Distribution Shift
Ahmad-Reza Ehyaei, Golnoosh Farnadi, Samira Samadi
Group-fairness metrics (e.g., equalized odds) can vary sharply across resamples and are especially brittle under distribution shift, undermining reliable audits. We propose a Wasse…
Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces
Ahmad-Reza Ehyaei, Kiarash Mohammadi, Amir-Hossein Karimi +2
As responsible AI gains importance in machine learning algorithms, properties such as fairness, adversarial robustness, and causality have received considerable attention in recent…
Robustness Implies Fairness in Causal Algorithmic Recourse
Ahmad-Reza Ehyaei, Amir-Hossein Karimi, Bernhard Schölkopf +1
Algorithmic recourse aims to disclose the inner workings of the black-box decision process in situations where decisions have significant consequences, by providing recommendations…