3 papers
cs.LG2022
Privacy-Preserving Machine Learning for Collaborative Data Sharing via Auto-encoder Latent Space Embeddings
Ana María Quintero-Ossa, Jesús Solano, Hernán Jarcía +3
Privacy-preserving machine learning in data-sharing processes is an ever-critical task that enables collaborative training of Machine Learning (ML) models without the need to share…
cs.LG2021
Enhancing User' s Income Estimation with Super-App Alternative Data
Gabriel Suarez, Juan Raful, Maria A. Luque +2
This paper presents the advantages of alternative data from Super-Apps to enhance user' s income estimation models. It compares the performance of these alternative data sources wi…
cs.LG2021
Supporting Financial Inclusion with Graph Machine Learning and Super-App Alternative Data
Luisa Roa, Andrés Rodríguez-Rey, Alejandro Correa-Bahnsen +1
The presence of Super-Apps have changed the way we think about the interactions between users and commerce. It then comes as no surprise that it is also redefining the way banking…