Gustavo Escobedo, Marta Moscati, Peter Müllner, Simone Kopeinik, Dominik Kowald, Elisabeth Lex, Markus Schedl
Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models
Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024), 2024

Gustavo Escobedo, Christian Ganhör, Stefan Brandl, Mirjam Augstein, Markus Schedl
Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training
Proceedings of the 5th International Workshop on Algorithmic Bias in Search and Recommendation (BIAS @ SIGIR 2024), 2024

Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekab-saz, Markus Schedl
Computational Versus Perceived Popularity Miscalibration in Recommender Systems
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023