Learning Sample-Specific Models with Low-Rank Personalized Regression

NeurIPS 2019 Benjamin LengerichBryon AragamEric P. Xing

Modern applications of machine learning (ML) deal with increasingly heterogeneous datasets comprised of data collected from overlapping latent subpopulations. As a result, traditional models trained over large datasets may fail to recognize highly predictive localized effects in favour of weakly predictive global patterns... (read more)

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