4.3k citations · 10.2k across the 68 of their papers we have counts for
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Top-K Off-Policy Correction for a REINFORCE Recommender System
Minmin Chen, Alex Beutel, Paul Covington +3
Industrial recommender systems deal with extremely large action spaces -- many millions of items to recommend. Moreover, they need to serve billions of users, who are unique at any…
Seq2Slate: Re-ranking and Slate Optimization with RNNs
Irwan Bello, Sayali Kulkarni, Sagar Jain +6
Ranking is a central task in machine learning and information retrieval. In this task, it is especially important to present the user with a slate of items that is appealing as a w…
Counterfactual Fairness in Text Classification through Robustness
Sahaj Garg, Vincent Perot, Nicole Limtiaco +3
In this paper, we study counterfactual fairness in text classification, which asks the question: How would the prediction change if the sensitive attribute referenced in the exampl…
Efficient Training on Very Large Corpora via Gramian Estimation
Walid Krichene, Nicolas Mayoraz, Steffen Rendle +5
We study the problem of learning similarity functions over very large corpora using neural network embedding models. These models are typically trained using SGD with sampling of r…