2 citations · 3 across the 4 of their papers we have counts for
5 papers
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…
Ranking Regularization for Critical Rare Classes: Minimizing False Positives at a High True Positive Rate
Mohammadi Kiarash, Zhao He, Mengyao Zhai +1
In many real-world settings, the critical class is rare and a missed detection carries a disproportionately high cost. For example, tumors are rare and a false negative diagnosis c…
FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms for Neural Networks
Kiarash Mohammadi, Aishwarya Sivaraman, Golnoosh Farnadi
Algorithmic decision making driven by neural networks has become very prominent in applications that directly affect people's quality of life. In this paper, we study the problem o…
Scaling Guarantees for Nearest Counterfactual Explanations
Kiarash Mohammadi, Amir-Hossein Karimi, Gilles Barthe +1
Counterfactual explanations (CFE) are being widely used to explain algorithmic decisions, especially in consequential decision-making contexts (e.g., loan approval or pretrial bail…
Faster Algorithms for Quantitative Analysis of Markov Chains and Markov Decision Processes with Small Treewidth
Ali Asadi, Krishnendu Chatterjee, Amir Kafshdar Goharshady +2
Discrete-time Markov Chains (MCs) and Markov Decision Processes (MDPs) are two standard formalisms in system analysis. Their main associated quantitative objectives are hitting pro…