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Emily Diana
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2020 – today
- 2024
- [c7]Siqi Deng, Emily Diana, Michael Kearns, Aaron Roth:
Balanced Filtering via Disclosure-Controlled Proxies. FORC 2024: 4:1-4:23 - [i11]Audrey Chang, Emily Diana, Alexander Williams Tolbert:
Reconciling Heterogeneous Effects in Causal Inference. CoRR abs/2406.03575 (2024) - [i10]Emily Diana, Alexander Williams Tolbert, Kavya Ravichandran, Avrim Blum:
Adaptive Algorithmic Interventions for Escaping Pessimism Traps in Dynamic Sequential Decisions. CoRR abs/2406.04462 (2024) - [i9]Emily Diana, Saeed Sharifi-Malvajerdi, Ali Vakilian:
Minimax Group Fairness in Strategic Classification. CoRR abs/2410.02513 (2024) - 2023
- [i8]Alexander Williams Tolbert, Emily Diana:
Correcting Underrepresentation and Intersectional Bias for Fair Classification. CoRR abs/2306.11112 (2023) - [i7]Siqi Deng, Emily Diana, Michael Kearns, Aaron Roth:
Balanced Filtering via Non-Disclosive Proxies. CoRR abs/2306.15083 (2023) - 2022
- [j1]Emily Diana, Mingzi Niu, Georgy Noarov:
SIGecom winter meeting 2022 highlights. SIGecom Exch. 20(1): 3-23 (2022) - [c6]Emily Diana, Wesley Gill, Michael Kearns, Krishnaram Kenthapadi, Aaron Roth
, Saeed Sharifi-Malvajerdi:
Multiaccurate Proxies for Downstream Fairness. FAccT 2022: 1207-1239 - 2021
- [c5]Emily Diana, Wesley Gill, Michael Kearns, Krishnaram Kenthapadi, Aaron Roth
Minimax Group Fairness: Algorithms and Experiments. AIES 2021: 66-76 - [c4]Emily Diana, Wesley Gill, Ira Globus-Harris, Michael Kearns, Aaron Roth
Lexicographically Fair Learning: Algorithms and Generalization. FORC 2021: 6:1-6:23 - [c3]Emily Diana, Travis Dick, Hadi Elzayn, Michael Kearns, Aaron Roth
Algorithms and Learning for Fair Portfolio Design. EC 2021: 371-389 - [i6]Emily Diana, Wesley Gill, Ira Globus-Harris, Michael Kearns, Aaron Roth, Saeed Sharifi-Malvajerdi:
Lexicographically Fair Learning: Algorithms and Generalization. CoRR abs/2102.08454 (2021) - [i5]Emily Diana, Wesley Gill, Michael Kearns, Krishnaram Kenthapadi, Aaron Roth, Saeed Sharifi-Malvajerdi:
Multiaccurate Proxies for Downstream Fairness. CoRR abs/2107.04423 (2021) - 2020
- [c2]Emily Diana, Michael Kearns, Seth Neel, Aaron Roth
Optimal, truthful, and private securities lending. ICAIF 2020: 48:1-48:8 - [c1]Emily Diana, Hadi Elzayn, Michael Kearns, Aaron Roth
Differentially Private Call Auctions and Market Impact. EC 2020: 541-583 - [i4]Emily Diana, Hadi Elzayn, Michael J. Kearns, Aaron Roth, Saeed Sharifi-Malvajerdi, Juba Ziani:
Differentially Private Call Auctions and Market Impact. CoRR abs/2002.05699 (2020) - [i3]Emily Diana, Travis Dick, Hadi Elzayn, Michael J. Kearns, Aaron Roth, Zachary Schutzman, Saeed Sharifi-Malvajerdi, Juba Ziani:
Algorithms and Learning for Fair Portfolio Design. CoRR abs/2006.07281 (2020) - [i2]Emily Diana, Wesley Gill, Michael Kearns, Krishnaram Kenthapadi, Aaron Roth:
Convergent Algorithms for (Relaxed) Minimax Fairness. CoRR abs/2011.03108 (2020)
2010 – 2019
- 2019
- [i1]Emily Diana, Michael J. Kearns, Seth Neel, Aaron Roth:
Optimal, Truthful, and Private Securities Lending. CoRR abs/1912.06202 (2019)
Coauthor Index
aka: Michael J. Kearns
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