FORC 2026: Accepted Papers

First Cycle:

Exact zCDP Characterizations for Fundamental Differentially Private Mechanisms
Charlie Harrison and Pasin Manurangsi

Nearly-Optimal Private Selection via Gaussian Mechanism
Ethan Leeman and Pasin Manurangsi

Fair Multi-agent Persuasion with Submodular Constraints
Yannan Bai, Kamesh Munagala, Yiheng Shen and Davidson Zhu

Tradeoffs in Privacy, Welfare, and Fairness for Facility Location
Sara Fish, Yannai A. Gonczarowski, Jason Z. Tang and Salil Vadhan

A Machine Learning Theory Perspective on Strategic Litigation
Melissa Dutz, Han Shao, Avrim Blum and Aloni Cohen

Incentivizing High-Quality Content in Online Recommender Systems
Xinyan Hu, Meena Jagadeesan, Michael Jordan and Jacob Steinhardt

Inducing Efficient and Equitable Professional Networks through Link Recommendations
Cynthia Dwork, Chris Hays, Lunjia Hu, Nicole Immorlica and Juan Perdomo

Normalized Square Root: Sharper Matrix Factorization Bounds for Differentially Private Continual Counting
Monika Henzinger, Nikita Kalinin and Jalaj Kumar Upadhyay

Can we Watermark Low-Entropy LLM Outputs?
Noam Mazor, Andrew Morgan and Rafael Pass

Learning Rate Scheduling with Matrix Factorization for Private Training
Nikita Kalinin and Joel Daniel Andersson