A Necessary and Sufficient Stability Notion for Adaptive Generalization. - Moshe Shenfeld; Katrina Ligett (NeurIPS, 2019)

A New Analysis of Differential Privacy's Generalization Guarantees. - Christopher Jung 001; Katrina Ligett; Seth Neel; Aaron Roth 001; Saeed Sharifi-Malvajerdi; Moshe Shenfeld (ITCS, 2020)

A new analysis of differential privacy's generalization guarantees (invited paper). - Christopher Jung 001; Katrina Ligett; Seth Neel; Aaron Roth 001; Saeed Sharifi-Malvajerdi; Moshe Shenfeld (STOC, 2021)

Generalization in the Face of Adaptivity: A Bayesian Perspective. - Moshe Shenfeld; Katrina Ligett (NeurIPS, 2023)

Privacy amplification by random allocation. - Vitaly Feldman; Moshe Shenfeld (CoRR, 2025)

How Well Can Differential Privacy Be Audited in One Run? - Amit Keinan; Moshe Shenfeld; Katrina Ligett (CoRR, 2025)

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches. - Omri Lev; Vishwak Srinivasan; Moshe Shenfeld; Katrina Ligett; Ayush Sekhari; Ashia C. Wilson (CoRR, 2025)