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Autor:
Massih-Reza Amini, Mikhail Trofimov, Charlotte Laclau, Yury Maximov, Oleh Horodnytskyi, Sumit Sidana
Publikováno v:
Data Mining and Knowledge Discovery. 35:568-592
In this paper, we propose a novel ranking framework for collaborative filtering with the overall aim of learning user preferences over items by minimizing a pairwise ranking loss. We show the minimization problem involves dependent random variables a