16 citations · 28 across the 4 of their papers we have counts for
10 papers
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…
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
Amir-Hossein Karimi, Gilles Barthe, Bernhard Schölkopf +1
Machine learning is increasingly used to inform decision-making in sensitive situations where decisions have consequential effects on individuals' lives. In these settings, in addi…
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
Amir-Hossein Karimi, Julius von Kügelgen, Bernhard Schölkopf +1
Recent work has discussed the limitations of counterfactual explanations to recommend actions for algorithmic recourse, and argued for the need of taking causal relationships betwe…
Algorithmic Recourse: from Counterfactual Explanations to Interventions
Amir-Hossein Karimi, Bernhard Schölkopf, Isabel Valera
As machine learning is increasingly used to inform consequential decision-making (e.g., pre-trial bail and loan approval), it becomes important to explain how the system arrived at…
Model-Agnostic Counterfactual Explanations for Consequential Decisions
Amir-Hossein Karimi, Gilles Barthe, Borja Balle +1
Predictive models are being increasingly used to support consequential decision making at the individual level in contexts such as pretrial bail and loan approval. As a result, the…
Deep Variational Sufficient Dimensionality Reduction
Ershad Banijamali, Amir-Hossein Karimi, Ali Ghodsi
We consider the problem of sufficient dimensionality reduction (SDR), where the high-dimensional observation is transformed to a low-dimensional sub-space in which the information…