3 papers
cs.IR2026
Value-Aware Product Recommendation by Customer Segmentation using a suitable High-Dimensional Similarity Measure
MarÃa Florencia Acosta, Rodrigo GarcÃa Arancibia, Pamela Llop +2
This paper presents a novel value-aware approach to product recommendation that simultaneously addresses the high dimensionality and sparsity of user-item data while explicitly inc…
cs.CV2026
ConfIC-RCA: Statistically Grounded Efficient Estimation of Segmentation Quality
Matias Cosarinsky, Ramiro Billot, Lucas Mansilla +5
Assessing the quality of automatic image segmentation is crucial in clinical practice, but often very challenging due to the limited availability of ground truth annotations. Rever…
cs.LG2025
BM-CL: Bias Mitigation through the lens of Continual Learning
Lucas Mansilla, Rodrigo Echeveste, Camila Gonzalez +2
Biases in machine learning pose significant challenges, particularly when models amplify disparities that affect disadvantaged groups. Traditional bias mitigation techniques often…