Web: http://arxiv.org/abs/2205.04701

May 11, 2022, 1:11 a.m. | Haoxuan Li, Chunyuan Zheng, Xiao-Hua Zhou, Peng Wu

cs.LG updates on arXiv.org arxiv.org

In recommender systems, users always choose favorite items to rate, which
results in data missing not at random and poses a great challenge for unbiased
evaluation and learning of prediction models. Currently, the doubly robust (DR)
method and its variants have been widely studied and demonstrate superior
performance. However, we show that DR methods are unstable to extremely small
propensities and rely on extrapolations, resulting in sub-optimal performances.
In this paper, we propose a stabilized doubly robust (SDR) estimator to …

arxiv data learning on random recommendation

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