Uncertainty-Adjusted Recommendation via Matrix Factorization With Weighted Losses-Reference-Cited by-同舟云学术

Uncertainty-Adjusted Recommendation via Matrix Factorization With Weighted Losses

Author:

Alves Rodrigo¹^ORCID,Ledent Antoine²^ORCID,Kloft Marius³^ORCID

Affiliation:

1. Department of Applied Mathematics, Czech Technical University in Prague (CTU), Prague, Czech Republic Prague

2. School of Computing and Information Sciences (SCIS), Singapore Management University (SMU), Singapore, Singapore

3. Department of Computer Science, University of Kaiserslautern-Landau (RPTU), Kaiserslautern, Germany

Funder

Recombee

Singapore Ministry of Education (MOE) Academic Research Fund (AcRF) Tier 1

Carl-Zeiss Foundation, the German Research Foundation

German Federal Ministry of Science and Education

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

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3. Uncertainty-adjusted Inductive Matrix Completion with Graph Neural Networks;Proceedings of the 17th ACM Conference on Recommender Systems;2023-09-14