Saeed Sharifi-Malvajerdi

According to our database, Saeed Sharifi-Malvajerdi authored at least 14 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Minimax Group Fairness in Strategic Classification.

Emily Diana, Saeed Sharifi-Malvajerdi, Ali Vakilian

CoRR, 2024

Bayesian Strategic Classification.

Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl, Ali Vakilian, Juba Ziani

CoRR, 2024

2023

Sequential Strategic Screening.

Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl, Ali Vakilian, Juba Ziani

Proceedings of the International Conference on Machine Learning, 2023

2022

Multiaccurate Proxies for Downstream Fairness.

Emily Diana, Wesley Gill, Michael Kearns, Krishnaram Kenthapadi, Aaron Roth, Saeed Sharifi-Malvajerdi

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021

A new analysis of differential privacy's generalization guarantees (invited paper).

Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld

Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Algorithms and Learning for Fair Portfolio Design.

Emily Diana, Travis Dick, Hadi Elzayn, Michael Kearns, Aaron Roth, Zachary Schutzman, Saeed Sharifi-Malvajerdi, Juba Ziani

Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

Adaptive Machine Unlearning.

Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Chris Waites

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Lexicographically Fair Learning: Algorithms and Generalization.

Emily Diana, Wesley Gill, Ira Globus-Harris, Michael Kearns, Aaron Roth, Saeed Sharifi-Malvajerdi

Proceedings of the 2nd Symposium on Foundations of Responsible Computing, 2021

Descent-to-Delete: Gradient-Based Methods for Machine Unlearning.

Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi

Proceedings of the Algorithmic Learning Theory, 2021

2020

Differentially Private Call Auctions and Market Impact.

Emily Diana, Hadi Elzayn, Michael Kearns, Aaron Roth, Saeed Sharifi-Malvajerdi, Juba Ziani

Proceedings of the EC '20: The 21st ACM Conference on Economics and Computation, 2020

A New Analysis of Differential Privacy's Generalization Guarantees.

Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld

Proceedings of the 11th Innovations in Theoretical Computer Science Conference, 2020

2019

Average Individual Fairness: Algorithms, Generalization and Experiments.

Saeed Sharifi-Malvajerdi, Michael J. Kearns, Aaron Roth

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Differentially Private Fair Learning.

Matthew Jagielski, Michael J. Kearns, Jieming Mao, Alina Oprea, Aaron Roth, Saeed Sharifi-Malvajerdi, Jonathan R. Ullman

Proceedings of the 36th International Conference on Machine Learning, 2019

2016

Analytical studies of fragmented-spectrum multi-level OFDM-CDMA technique in cognitive radio networks.

Farhad Akhoundi, Saeed Sharifi-Malvajerdi, Omid Poursaeed, Jawad A. Salehi

Proceedings of the 7th IEEE Annual Ubiquitous Computing, 2016