Search Results for author: Sirui Yao

Found 3 papers, 1 papers with code

Beyond Parity: Fairness Objectives for Collaborative Filtering

1 code implementation NeurIPS 2017 Sirui Yao, Bert Huang

We study fairness in collaborative-filtering recommender systems, which are sensitive to discrimination that exists in historical data.

Collaborative Filtering Fairness +1

New Fairness Metrics for Recommendation that Embrace Differences

no code implementations29 Jun 2017 Sirui Yao, Bert Huang

We study fairness in collaborative-filtering recommender systems, which are sensitive to discrimination that exists in historical data.

Collaborative Filtering Fairness +1

Measuring Recommender System Effects with Simulated Users

no code implementations12 Jan 2021 Sirui Yao, Yoni Halpern, Nithum Thain, Xuezhi Wang, Kang Lee, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel

Using this simulation framework, we can (a) isolate the effect of the recommender system from the user preferences, and (b) examine how the system performs not just on average for an "average user" but also the extreme experiences under atypical user behavior.

Collaborative Filtering Recommendation Systems

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