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20182026
most citedAre We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches

424 citations · 855 across the 27 of their papers we have counts for

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cs.LG2024★ 1 cited

Automated Off-Policy Estimator Selection via Supervised Learning

Nicolò Felicioni, Michael Benigni, Maurizio Ferrari Dacrema

The Off-Policy Evaluation (OPE) problem consists of evaluating the performance of counterfactual policies with data collected by another one. To solve the OPE problem, we resort to…