Jamie Morgenstern
University of Washington
H-index: 28
North America-United States
Top articles of Jamie Morgenstern
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Emergent specialization from participation dynamics and multi-learner retraining | Sarah Dean Mihaela Curmei Lillian Ratliff Jamie Morgenstern Maryam Fazel | 2024/4/18 | |
Scalable membership inference attacks via quantile regression | Advances in Neural Information Processing Systems | Martin Bertran Shuai Tang Aaron Roth Michael Kearns Jamie H Morgenstern | 2024/2/13 |
Doubly Constrained Fair Clustering | Advances in Neural Information Processing Systems | John Dickerson Seyed Esmaeili Jamie H Morgenstern Claire Jie Zhang | 2024/2/13 |
Large language models cannot replace human participants because they cannot portray identity groups | arXiv preprint arXiv:2402.01908 | Angelina Wang Jamie Morgenstern John P Dickerson | 2024/2/2 |
Distributionally Robust Data Join | arXiv preprint arXiv:2202.05797 | Pranjal Awasthi Christopher Jung Jamie Morgenstern | 2022/2/11 |
Initializing Services in Interactive ML Systems for Diverse Users | arXiv preprint arXiv:2312.11846 | Avinandan Bose Mihaela Curmei Daniel L Jiang Jamie Morgenstern Sarah Dean | 2023/12/19 |
Fair Active Learning in Low-Data Regimes | arXiv preprint arXiv:2312.08559 | Romain Camilleri Andrew Wagenmaker Jamie Morgenstern Lalit Jain Kevin Jamieson | 2023/12/13 |
Changing distributions and preferences in learning systems | Jamie Morgenstern | 2023/8/8 | |
Evaluation of targeted dataset collection on racial equity in face recognition | Rachel Hong Tadayoshi Kohno Jamie Morgenstern | 2023 | |
Multicalibrated regression for downstream fairness | Ira Globus-Harris Varun Gupta Christopher Jung Michael Kearns Jamie Morgenstern | 2023/8/8 | |
Optimal spend rate estimation and pacing for ad campaigns with budgets | arXiv preprint arXiv:2202.05881 | Bhuvesh Kumar Jamie Morgenstern Okke Schrijvers | 2022/2/4 |
Active learning with safety constraints | Advances in Neural Information Processing Systems | Romain Camilleri Andrew Wagenmaker Jamie H Morgenstern Lalit Jain Kevin G Jamieson | 2022/12/6 |
Fairness in clustering | Brian Brubach Deeparnab Chakrabarty John P Dickerson MK Seyed Esmaeili M Knittel | 2022 | |
Preference dynamics under personalized recommendations | Sarah Dean Jamie Morgenstern | 2022/7/12 | |
Fairness in prediction and allocation | Online and matching-based market design. Cambridge University Press (forthcoming) | Jamie Morgenstern Aaron Roth | 2022 |
Multi-learner risk reduction under endogenous participation dynamics | arXiv preprint arXiv:2206.02667 | Sarah Dean Mihaela Curmei Lillian J Ratliff Jamie Morgenstern Maryam Fazel | 2022/6/6 |
Excerpt from datasheets for datasets | Timnit Gebru Jamie Morgenstern Briana Vecchione Jennifer Wortman Vaughan Hanna Wallach | 2022/5/12 | |
Auctions and Peer Prediction for Scientific Peer Review | ArXivorg | Siddarth Srinivasan Jamie Morgenstern | 2021/8 |
Evaluating fairness of machine learning models under uncertain and incomplete information | Pranjal Awasthi Alex Beutel Matthäus Kleindessner Jamie Morgenstern Xuezhi Wang | 2021/3/3 | |
Auctions and prediction markets for scientific peer review | arXiv preprint arXiv:2109.00923 | Siddarth Srinivasan Jamie Morgenstern | 2021 |
Co-Authors
