1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 1 cited
Feasible and Desirable Counterfactual Generation by Preserving Human Defined Constraints
Homayun Afrabandpey, Michael Spranger
We present a human-in-the-loop approach to generate counterfactual (CF) explanations that preserve global and local feasibility constraints. Global feasibility constraints refer to…
cs.LG2019
A Decision-Theoretic Approach for Model Interpretability in Bayesian Framework
Homayun Afrabandpey, Tomi Peltola, Juho Piironen +2
A salient approach to interpretable machine learning is to restrict modeling to simple models. In the Bayesian framework, this can be pursued by restricting the model structure and…
cs.LG2019
Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets
Homayun Afrabandpey, Tomi Peltola, Samuel Kaski
Learning predictive models from small high-dimensional data sets is a key problem in high-dimensional statistics. Expert knowledge elicitation can help, and a strong line of work f…