FORC 2026 Program

Wednesday, June 3, 2026

Location: Science & Engineering Complex – 150 Western Ave, Allston, MA 02134

8:00 AM–9:00 AM Breakfast

9:00 AM–10:15 AM Session 1

Normalized Square Root: Sharper Matrix Factorization Bounds for Differentially Private Continual Counting
M. Henzinger, N. Kalinin, J. Upadhyay

No One Size Fits All: Exploring Heterogeneous Differential Privacy
M. Aliakbarpour, A. Fallah, S. Roy, R. Stevens

Exact zCDP Characterizations for Fundamental Differentially Private Mechanisms
C. Harrison, P. Manurangsi

Optimal partition selection with Rényi differential privacy
C. Harrison, P. Manurangsi

10:15 AM–10:45 AM Coffee Break

10:45 AM–12:00 PM Award Session I

Best Paper Award

Nearly-Optimal Private Selection via Gaussian Mechanism
E. Leeman, P. Manurangsi

A Machine Learning Theory Perspective on Strategic Litigation
M. Dutz, H. Shao, A. Blum, A. Cohen

The Importance of Being Smoothly Calibrated
P. Gopalan, K. Stavropoulos, K. Talwar, P. Tankala

Best Paper Award, Honorable Mention

Limitations on Accurate, Trusted, Human-level Reasoning
R. Panigrahy, V. Sharan

12:00 PM–2:00 PM Lunch

2:00 PM–3:15 PM Session 3

When to Ask a Question: Understanding Communication Strategies in Generative AI Tools
C. Park, K. Donahue, M. Raghavan

Serving Clients Fairly: On Facility Location and $k$-Median with Fair Outliers
R. Dabas, S. Khuller, E. Rivkin

Reliable Abstention under Adversarial Injections: Tight Lower Bounds and New Upper Bounds
E. Edelman, S. Goel

Defensive Generation
G. Farina, J. Perdomo

3:15 PM–3:45 PM Coffee Break

3:45 PM–5:00 PM Poster Session

5:15 PM–5:45 PM Business Meeting

Thursday, June 4th, 2026

Location: Science & Engineering Complex – 150 Western Ave, Allston, MA 02134

8:00 AM–9:00 AM Breakfast

9:00 AM–10:15 AM Award Session II

Best Student Paper Award

Incentivizing High-Quality Content in Online Recommender Systems
X. Hu, M. Jagadeesan, M. Jordan, J. Steinhardt

Inducing Efficient and Equitable Professional Networks through Link Recommendations
C. Dwork, C. Hays, L. Hu, N. Immorlica, J. Perdomo

Best Paper Award, Honorable Mention

Computational Hardness of Private Coreset
B. Ghazi, C. Guzmán, P. Kamath, A. Knop, R. Kumar, P. Manurangsi

Protecting the Undeleted in Machine Unlearning
A. Cohen, R. Kohen, K. Nissim, U. Stemmer

10:15 AM–10:45 AM Coffee Break

10:45 AM–11:45 AM Session 2

Invited Talk by Shafi Goldwasser

11:45 AM–2:00 PM Lunch

2:00 PM–3:15 PM Session 3

The Statistical Fairness-Accuracy Frontier
A. Fallah, M. Jordan, A. Ulichney

Can Users Fix Algorithms? A Game-Theoretic Analysis of Collective Content Amplification in Recommender Systems
E. Fedorova, M. Kitch, C. Podimata

How Global Calibration Strengthens Multiaccuracy
S. Casacuberta, P. Gopalan, V. Kanade, O. Reingold

Understanding and Mitigating the Impacts of Differentially Private Census Data on State Level Redistricting & Looking Ahead to the 2030 Census
C. Cianfarani, A. Cohen

3:15 PM–3:45 PM Coffee Break

3:45 PM–5:00 PM Session 4

Learning in an Echo Chamber: Online Learning with Replay Adversary
D. Dmitriev, H. Franck, C. Heinzler, A. Sanyal

On the Limits of Language Generation: Trade-Offs Between Hallucination and Mode Collapse
A. Kalavasis, A. Mehrotra, G. Velegkas

Can we Watermark Low-Entropy LLM Outputs?
N. Mazor, A. Morgan, R. Pass

How Sampling Shapes LLM Alignment: From One-Shot Optima to Iterative Dynamics
Y. Chen, Y. He, M. Jordan, F. Yao

Friday, June 5th, 2026

Location: Science & Engineering Complex – 150 Western Ave, Allston, MA 02134

8:00 AM–9:00 AM Breakfast

9:00 AM–10:15 AM Session 1

Local Node Differential Privacy
S. Raskhodnikova, A. Smith, C. Wagaman, A. Zavyalov

A Differentially Private Approximation of the Width Problem
M. Hale, O. Sheffet

Separating Oblivious and Adaptive Differential Privacy under Continual Observation
M. Bun, M. Gaboardi, C. Wagaman

Privacy amplification by random allocation
M. Shenfeld, V. Feldman

10:15 AM–10:45 AM Coffee Break

10:45 AM–12:00 PM Session 2

Invited Talk by Ariel Procaccia

12:00 PM–2:00 PM Lunch

2:00 PM–3:15 PM Session 3

Trade-offs in Data Memorization via Strong Data Processing Inequalities
V. Feldman, G. Kornowski, X. Lyu

Learning Rate Scheduling with Matrix Factorization for Private Training
N. Kalinin, J. Andersson

Tradeoffs in Privacy, Welfare, and Fairness for Facility Location
S. Fish, Y. Gonczarowski, J. Tang, S. Vadhan

Privacy, Prediction, and Allocation
B. Jacobsen, N. Kohli

3:15 PM–3:45 PM Coffee Break

3:45 PM–5:00 PM Session 4

Fair Multi-agent Persuasion with Submodular Constraints
Y. Bai, K. Munagala, Y. Shen, D. Zhu

Packing Compact Subgraphs with Applications to Districting
H. Chen, P. Chou, P. Dharangutte, J. Gao, S. Huang, F. Yu

Two papers on risk-aware hypothesis testing — Nomination for FORC 2026 Highlights Track
F. Shi, S. Bates, M. Wainwright

Escaping the Subprime Trap in Algorithmic Lending
A. Bouyamourn, A. Tolbert