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…
stat.ME2026
A semiparametric autorregresive spatial prediction model
Rodrigo GarcÃa Arancibia, Pamela Llop, Mariel Lovatto
In this paper we propose a semiparametric spatial autoregressive model that combines a linear covariate component with a nonparametrically estimated spatial term, allowing flexible…
stat.ME2025
Sufficient dimension reduction for regression with spatially correlated errors: application to prediction
Liliana Forzani, Rodrigo GarcÃa Arancibia, Antonella Gieco +2
In this paper, we address the problem of predicting a response variable in the context of both, spatially correlated and high-dimensional data. To reduce the dimensionality of the…