22 citations · 61 across the 5 of their papers we have counts for
3 papers · 1 filter
The Stereotyping Problem in Collaboratively Filtered Recommender Systems
Wenshuo Guo, Karl Krauth, Michael I. Jordan +1
Recommender systems play a crucial role in mediating our access to online information. We show that such algorithms induce a particular kind of stereotyping: if preferences for a s…
Do Offline Metrics Predict Online Performance in Recommender Systems?
Karl Krauth, Sarah Dean, Alex Zhao +4
Recommender systems operate in an inherently dynamical setting. Past recommendations influence future behavior, including which data points are observed and how user preferences ch…
Exploration in two-stage recommender systems
Jiri Hron, Karl Krauth, Michael I. Jordan +1
Two-stage recommender systems are widely adopted in industry due to their scalability and maintainability. These systems produce recommendations in two steps: (i) multiple nominato…