2 papers
cs.LG2025
DISCO: A Browser-Based Privacy-Preserving Framework for Distributed Collaborative Learning
Julien T. T. Vignoud, Valérian Rousset, Hugo El Guedj +28
Data is often impractical to share for a range of well considered reasons, such as concerns over privacy, intellectual property, and legal constraints. This not only fragments the…
cs.IR2021
Recommending Burgers based on Pizza Preferences: Addressing Data Sparsity with a Product of Experts
Martin Milenkoski, Diego Antognini, Claudiu Musat
In this paper, we describe a method to tackle data sparsity and create recommendations in domains with limited knowledge about user preferences. We expand the variational autoencod…