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Factorized Structured Regression for Large-Scale Varying Coefficient Models. (arXiv:2205.13080v1 [stat.ML])
May 27, 2022, 1:11 a.m. | David Rügamer, Andreas Bender, Simon Wiegrebe, Daniel Racek, Bernd Bischl, Christian L. Müller, Clemens Stachl
stat.ML updates on arXiv.org arxiv.org
Recommender Systems (RS) pervade many aspects of our everyday digital life.
Proposed to work at scale, state-of-the-art RS allow the modeling of thousands
of interactions and facilitate highly individualized recommendations.
Conceptually, many RS can be viewed as instances of statistical regression
models that incorporate complex feature effects and potentially non-Gaussian
outcomes. Such structured regression models, including time-aware varying
coefficients models, are, however, limited in their applicability to
categorical effects and inclusion of a large number of interactions. Here, we
propose …
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