Lex Beattie

According to our database, Lex Beattie authored at least 7 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Building Human Values into Recommender Systems: An Interdisciplinary Synthesis.

Jonathan Stray, Alon Y. Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Chloé Bakalar, Lex Beattie, Michael D. Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy Xian Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan

Trans. Recomm. Syst., September, 2024

Not Just Algorithms: Strategically Addressing Consumer Impacts in Information Retrieval.

Michael D. Ekstrand, Lex Beattie, Maria Soledad Pera, Henriette Cramer

Proceedings of the Advances in Information Retrieval, 2024

2023

Evaluation Framework for Understanding Sensitive Attribute Association Bias in Latent Factor Recommendation Algorithms.

Lex Beattie, Isabel Corpus, Lucy H. Lin, Praveen Ravichandran

CoRR, 2023

Scoping Fairness Objectives and Identifying Fairness Metrics for Recommender Systems: The Practitioners' Perspective.

Jessie J. Smith, Lex Beattie, Henriette Cramer

Proceedings of the ACM Web Conference 2023, 2023

2022

RecSys Fairness Metrics: Many to Use But Which One To Choose?

Jessie J. Smith, Lex Beattie

CoRR, 2022

Building Human Values into Recommender Systems: An Interdisciplinary Synthesis.

Jonathan Stray, Alon Y. Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Lex Beattie, Michael D. Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy X. Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan

CoRR, 2022

Challenges in Translating Research to Practice for Evaluating Fairness and Bias in Recommendation Systems.

Lex Beattie, Dan Taber, Henriette Cramer

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022