1.1k citations · 4.8k across the 64 of their papers we have counts for
5 papers · 1 filter
Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics
Guy Tennenholtz, Martin Mladenov, Nadav Merlis +2
While popularity bias is recognized to play a crucial role in recommmender (and other ranking-based) systems, detailed analysis of its impact on collective user welfare has largely…
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis
Jonathan Stray, Alon Halevy, Parisa Assar +18
Recommender systems are the algorithms which select, filter, and personalize content across many of the worlds largest platforms and apps. As such, their positive and negative effe…
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…
Active Collaborative Filtering
Craig Boutilier, Richard S. Zemel, Benjamin Marlin
Collaborative filtering (CF) allows the preferences of multiple users to be pooled to make recommendations regarding unseen products. We consider in this paper the problem of onlin…
A Framework for Optimizing Paper Matching
Laurent Charlin, Richard S. Zemel, Craig Boutilier
At the heart of many scientific conferences is the problem of matching submitted papers to suitable reviewers. Arriving at a good assignment is a major and important challenge for…