5 citations · 5 across the 4 of their papers we have counts for
4 papers
A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems
Mohammad-Amin Charusaie, Samira Samadi
Learn-to-Defer is a paradigm that enables learning algorithms to work not in isolation but as a team with human experts. In this paradigm, we permit the system to defer a subset of…
The Role of Learning Algorithms in Collective Action
Omri Ben-Dov, Jake Fawkes, Samira Samadi +1
Collective action in machine learning is the study of the control that a coordinated group can have over machine learning algorithms. While previous research has concentrated on as…
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…
Sample Efficient Learning of Predictors that Complement Humans
Mohammad-Amin Charusaie, Hussein Mozannar, David Sontag +1
One of the goals of learning algorithms is to complement and reduce the burden on human decision makers. The expert deferral setting wherein an algorithm can either predict on its…