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Journal Articles
- 2022
[j2]Nasim Sonboli
, Robin Burke, Michael D. Ekstrand, Rishabh Mehrotra:
The Multisided Complexity of Fairness in Recommender Systems. AI Mag. 43(2): 164-176 (2022)- 2019
- [j1]Bamshad Mobasher, Lucia Dettori, Daniela Raicu, Raffaella Settimi, Nasim Sonboli, Monica Stettler:
Data Science Summer Academy for Chicago Public School Students. SIGKDD Explor. 21(1): 49-52 (2019)
Conference and Workshop Papers
- 2023
- [c20]Michael D. Ekstrand, Jean Garcia-Gathright, Nasim Sonboli, Amifa Raj, Karlijn Dinnissen:
FAccTRec 2023: The 6th Workshop on Responsible Recommendation. RecSys 2023: 1267-1268 - 2022
- [c19]Mohammadmehdi Naghiaei, Hossein A. Rahmani, Mohammad Aliannejadi, Nasim Sonboli:
Towards Confidence-aware Calibrated Recommendation. CIKM 2022: 4344-4348 - [c18]Nasim Sonboli, Toshihiro Kamishima, Amifa Raj, Luca Belli, Robin Burke:
FAccTRec 2022: The 5th Workshop on Responsible Recommendation. RecSys 2022: 686-687 - [c17]Styliani Kleanthous, Bamshad Mobasher, Tsvika Kuflik, Bettina Berendt, Robin Burke, Jahna Otterbacher, Nasim Sonboli, Avital Shulner-Tal:
5th Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2022). UMAP (Adjunct Publication) 2022: 209-210 - [c16]Robin Burke, Nicholas Mattei, Vladislav Grozin, Amy Voida, Nasim Sonboli:
Multi-agent Social Choice for Dynamic Fairness-aware Recommendation. UMAP (Adjunct Publication) 2022: 234-244 - 2021
- [c15]Nasim Sonboli, Masoud Mansoury, Ziyue Guo, Shreyas Kadekodi, Weiwen Liu, Zijun Liu, Andrew Schwartz, Robin Burke:
librec-auto: A Tool for Recommender Systems Experimentation. CIKM 2021: 4584-4593 - [c14]Michael D. Ekstrand, Pierre-Nicolas Schwab, Toshihiro Kamishima, Nasim Sonboli:
FAccTRec 2021: The 4th Workshop on Responsible Recommendation. RecSys 2021: 778-779 - [c13]Nasim Sonboli, Jessie J. Smith, Florencia Cabral Berenfus, Robin Burke, Casey Fiesler:
Fairness and Transparency in Recommendation: The Users' Perspective. UMAP 2021: 274-279 - 2020
- [c12]Robin D. Burke, Masoud Mansoury, Nasim Sonboli:
Experimentation with fairness-aware recommendation using librec-auto: hands-on tutorial. FAT* 2020: 700 - [c11]Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke:
Calibration in Collaborative Filtering Recommender Systems: a User-Centered Analysis. HT 2020: 197-206 - [c10]Nasim Sonboli, Robin Burke, Zijun Liu, Masoud Mansoury:
Fairness-aware Recommendation with librec-auto. RecSys 2020: 594-596 - [c9]Michael D. Ekstrand, Pierre-Nicolas Schwab, Jean Garcia-Gathright, Toshihiro Kamishima, Nasim Sonboli:
3rd FAccTRec Workshop: Responsible Recommendation. RecSys 2020: 607-608 - [c8]Nasim Sonboli, Farzad Eskandanian, Robin Burke, Weiwen Liu, Bamshad Mobasher:
Opportunistic Multi-aspect Fairness through Personalized Re-ranking. UMAP 2020: 239-247 - [c7]Diego Sánchez-Moreno, María N. Moreno García, Nasim Sonboli, Bamshad Mobasher, Robin Burke:
Using Social Tag Embedding in a Collaborative Filtering Approach for Recommender Systems. WI/IAT 2020: 502-507 - 2019
- [c6]Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke:
Crank up the Volume: Preference Bias Amplification in Collaborative Recommendation. RMSE@RecSys 2019 - [c5]Weiwen Liu, Jun Guo, Nasim Sonboli, Robin Burke, Shengyu Zhang:
Personalized fairness-aware re-ranking for microlending. RecSys 2019: 467-471 - [c4]Farzad Eskandanian, Nasim Sonboli, Bamshad Mobasher:
Power of the Few: Analyzing the Impact of Influential Users in Collaborative Recommender Systems. UMAP 2019: 225-233 - [c3]Nasim Sonboli, Robin Burke:
Localized Fairness in Recommender Systems. UMAP (Adjunct Publication) 2019: 295-300 - 2018
- [c2]Robin Burke, Nasim Sonboli, Aldo Ordonez-Gauger:
Balanced Neighborhoods for Multi-sided Fairness in Recommendation. FAT 2018: 202-214 - [c1]Diego Sánchez-Moreno, María N. Moreno García, Nasim Sonboli, Bamshad Mobasher, Robin Burke:
Inferring User Expertise from Social Tagging in Music Recommender Systems for Streaming Services. HAIS 2018: 39-49
Informal and Other Publications
- 2024
- [i9]Suresh Venkatasubramanian, Timnit Gebru, Ufuk Topcu, Haley Griffin, Leah Namisa Rosenbloom, Nasim Sonboli:
Community Driven Approaches to Research in Technology & Society CCC Workshop Report. CoRR abs/2406.07556 (2024) - 2022
- [i8]Mohammadmehdi Naghiaei, Hossein A. Rahmani, Mohammad Aliannejadi, Nasim Sonboli:
Towards Confidence-aware Calibrated Recommendation. CoRR abs/2208.10192 (2022) - 2021
- [i7]Nasim Sonboli, Jessie J. Smith, Florencia Cabral Berenfus, Robin Burke, Casey Fiesler:
Fairness and Transparency in Recommendation: The Users' Perspective. CoRR abs/2103.08786 (2021) - 2020
- [i6]Jessie Smith, Nasim Sonboli, Casey Fiesler, Robin Burke:
Exploring User Opinions of Fairness in Recommender Systems. CoRR abs/2003.06461 (2020) - [i5]Nasim Sonboli, Farzad Eskandanian, Robin Burke, Weiwen Liu, Bamshad Mobasher:
Opportunistic Multi-aspect Fairness through Personalized Re-ranking. CoRR abs/2005.12974 (2020) - [i4]Nasim Sonboli, Robin Burke, Nicholas Mattei, Farzad Eskandanian, Tian Gao:
"And the Winner Is...": Dynamic Lotteries for Multi-group Fairness-Aware Recommendation. CoRR abs/2009.02590 (2020) - 2019
- [i3]Farzad Eskandanian, Nasim Sonboli, Bamshad Mobasher:
Power of the Few: Analyzing the Impact of Influential Users in Collaborative Recommender Systems. CoRR abs/1905.08031 (2019) - [i2]Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke:
Crank up the volume: preference bias amplification in collaborative recommendation. CoRR abs/1909.06362 (2019) - 2018
- [i1]Robin Burke, Jackson Kontny, Nasim Sonboli:
Synthetic Attribute Data for Evaluating Consumer-side Fairness. CoRR abs/1809.04199 (2018)
Coauthor Index
aka: Robin Burke
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