2 papers
cs.IR2024
On the challenges of studying bias in Recommender Systems: A UserKNN case study
Savvina Daniil, Manel Slokom, Mirjam Cuper +3
Statements on the propagation of bias by recommender systems are often hard to verify or falsify. Research on bias tends to draw from a small pool of publicly available datasets an…
cs.LG2023
Faithful Model Explanations through Energy-Constrained Conformal Counterfactuals
Patrick Altmeyer, Mojtaba Farmanbar, Arie van Deursen +1
Counterfactual explanations offer an intuitive and straightforward way to explain black-box models and offer algorithmic recourse to individuals. To address the need for plausible…