Evaluating Stochastic Rankings with Expected Exposure-Reference-Cited by-同舟云学术

Evaluating Stochastic Rankings with Expected Exposure

Published:2020-10-19 Issue: Volume: Page:
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Container-title:Proceedings of the 29th ACM International Conference on Information & Knowledge Management
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Author:

Diaz Fernando¹,Mitra Bhaskar²,Ekstrand Michael D.³,Biega Asia J.¹,Carterette Ben⁴

Affiliation:

1. Microsoft, Montréal, PQ, Canada

2. Microsoft, Montréal, PQ, United Kingdom

3. Boise State University, Boise, ID, USA

4. Spotify, New York, NY, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3340531.3411962

Reference49 articles.

1. Yoshua Bengio Nicholas Léonard and Aaron Courville. 2013. Estimating or propagating gradients through stochastic neurons for conditional computation. arXiv preprint arXiv:1308.3432 (2013). Yoshua Bengio Nicholas Léonard and Aaron Courville. 2013. Estimating or propagating gradients through stochastic neurons for conditional computation. arXiv preprint arXiv:1308.3432 (2013).

2. Fairness in Recommendation Ranking through Pairwise Comparisons

3. Equity of Attention

4. A Stochastic Treatment of Learning to Rank Scoring Functions

5. Learning to rank using gradient descent

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