11 citations · 23 across the 6 of their papers we have counts for
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stat.ML2017★ 2 cited
An interpretable latent variable model for attribute applicability in the Amazon catalogue
Tammo Rukat, Dustin Lange, Cédric Archambeau
Learning attribute applicability of products in the Amazon catalog (e.g., predicting that a shoe should have a value for size, but not for battery-type at scale is a challenge. The…
stat.ML2017★ 11 cited
Bayesian Boolean Matrix Factorisation
Tammo Rukat, Chris C. Holmes, Michalis K. Titsias +1
Boolean matrix factorisation aims to decompose a binary data matrix into an approximate Boolean product of two low rank, binary matrices: one containing meaningful patterns, the ot…