Binary Matrix Completion Using Unobserved Entries

13 Mar 2018Masayoshi HayashiTomoya SakaiMasashi Sugiyama

A matrix completion problem, which aims to recover a complete matrix from its partial observations, is one of the important problems in the machine learning field and has been studied actively. However, there is a discrepancy between the mainstream problem setting, which assumes continuous-valued observations, and some practical applications such as recommendation systems and SNS link predictions where observations take discrete or even binary values... (read more)

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