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Olivier Gouvert

2 accepted papers

2020

Ordinal Non-negative Matrix Factorization for Recommendation

ICML 2020poster

We introduce a new non-negative matrix factorization (NMF) method for ordinal data, called OrdNMF. Ordinal data are categorical data which exhibit a natural ordering between the categories. In particular, they can be found in recommender systems, either with explicit data (such as ratings) or implic…

2019

Recommendation from Raw Data with Adaptive Compound Poisson Factorization

UAI 2019poster

Count data are often used in recommender systems: they are widespread (song play counts, product purchases, clicks on web pages) and can reveal user preference without any explicit rating from the user. Such data are known to be sparse, over-dispersed and bursty, which makes their direct use in reco…