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cs.IR2022
Learning over No-Preferred and Preferred Sequence of Items for Robust Recommendation (Extended Abstract)
Aleksandra Burashnikova, Yury Maximov, Marianne Clausel +3
This paper is an extended version of [Burashnikova et al., 2021, arXiv: 2012.06910], where we proposed a theoretically supported sequential strategy for training a large-scale Reco…
cs.IR2021
Recommender systems: when memory matters
Aleksandra Burashnikova, Marianne Clausel, Massih-Reza Amini +2
In this paper, we study the effect of long memory in the learnability of a sequential recommender system including users' implicit feedback. We propose an online algorithm, where m…
cs.IR2020
Learning over no-Preferred and Preferred Sequence of items for Robust Recommendation
Aleksandra Burashnikova, Marianne Clausel, Charlotte Laclau +3
In this paper, we propose a theoretically founded sequential strategy for training large-scale Recommender Systems (RS) over implicit feedback, mainly in the form of clicks. The pr…