Year: 2021
Type: conference-paper
Abstract: Machine learning models may perform differently on different data subgroups, which we represent as itemsets (i.e., conjunctions of simple predicates). The identification of these critical data subgroups plays an important role in many applications, for example model validation and testing, or evaluation of model fairness. Typically, domain expert help is required to identify relevant (or sensitive) subgroups.
Authors: Eliana Pastor, Luca de Alfaro, Elena Baralis
Institutions: Politecnico di Torino, University of California, Santa Cruz
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3173173856