Orthogonal inductive matrix completion

• Main Authors: LEDENT, Antoine, ALVES, Rrodrigo, KLOFT, Marius
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Optimization; Recommender systems; Training; Social networking (online); Predictive models; Learning systems; Machine learning; recommender systems; statistical learning; Artificial Intelligence and Robotics
• Online Access: https://ink.library.smu.edu.sg/sis_research/7197; https://ink.library.smu.edu.sg/context/sis_research/article/8200/viewcontent/2004.01653.pdf
• Institution: Singapore Management University

We propose orthogonal inductive matrix completion (OMIC), an interpretable approach to matrix completion based on a sum of multiple orthonormal side information terms, together with nuclear-norm regularization. The approach allows us to inject prior knowledge about the singular vectors of the ground...