Probabilistic Error Guarantees for Abductive Inference

Bounded-confidence cascades simulate the spread of ideas on a social network. Fitting these models with social media datasets would let us study the mechanics of online political polarization. However, bounded-confidence model fitting is largely unexplored by the field due to incompatibility between messy, real datasets and the model’s abstract foundations.

[Paper][Presentation]: Pang-Naylor, K., Li, I., Rajesh, K., Montañez, G. D. (2024). Probabilistic Error Guarantees for Abductive Inference. IEEE International Conference on Future Machine Learning and Data Science (IEEE FMLDS). doi:10.1109/fmlds63805.2024.00038.