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Found 5 papers, 3 papers with code
Exploiting Preference Elicitation in Interactive and User-centered Algorithmic Recourse: An Initial Exploration
Our results suggest that users may recognize that the guided interaction paradigm improves efficiency.
Personalized Algorithmic Recourse with Preference Elicitation
It is paramount that the sequence of actions does not require too much effort for users to implement.
Synthesizing explainable counterfactual policies for algorithmic recourse with program synthesis
Being able to provide counterfactual interventions - sequences of actions we would have had to take for a desirable outcome to happen - is essential to explain how to change an unfavourable decision by a black-box machine learning model (e. g., being denied a loan request).
Learning compositional programs with arguments and sampling
We showcase the potential of our approach by learning the Quicksort algorithm, showing how the ability to deal with arguments is crucial for learning and generalization.
A general method for estimating the prevalence of Influenza-Like-Symptoms with Wikipedia data
Influenza is an acute respiratory seasonal disease that affects millions of people worldwide and causes thousands of deaths in Europe alone.
