Recommendations as Treatments: Debiasing Learning and EvaluationDownload PDFOpen Website

2016 (modified: 11 Nov 2022)ICML 2016Readers: Everyone
Abstract: Most data for evaluating and training recommender systems is subject to selection biases, either through self-selection by the users or through the actions of the recommendation system itself. In t...
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