Moshe Shenfeld

13 papers A* 3A 1Journal 9
YearRankTypeTitle / Venue / Authors
2026 J jnl
Efficient privacy loss accounting for subsampling and random allocation.
CoRR
Vitaly Feldman, Moshe Shenfeld
2026 J jnl
Near-Optimal Private Linear Regression via Iterative Hessian Mixing.
CoRR
Omri Lev, Moshe Shenfeld, Vishwak Srinivasan, Katrina Ligett, Ashia C. Wilson
2025 J jnl
Black-Box Differentially Private Nonparametric Confidence Intervals Under Minimal Assumptions.
CoRR
Tomer Shoham, Moshe Shenfeld, Noa Velner-Harris, Katrina Ligett
2025 J jnl
How Well Can Differential Privacy Be Audited in One Run?
CoRR
Amit Keinan, Moshe Shenfeld, Katrina Ligett
2025 J jnl
Privacy amplification by random allocation.
CoRR
Vitaly Feldman, Moshe Shenfeld
2025 J jnl
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches.
CoRR
Omri Lev, Vishwak Srinivasan, Moshe Shenfeld, Katrina Ligett, Ayush Sekhari, Ashia C. Wilson
2023 A* conf
Generalization in the Face of Adaptivity: A Bayesian Perspective.
NeurIPS
Moshe Shenfeld, Katrina Ligett
2021 A* conf
A new analysis of differential privacy's generalization guarantees (invited paper).
STOC
Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld
2021 J jnl
Generalization in the Face of Adaptivity: A Bayesian Perspective.
CoRR
Moshe Shenfeld, Katrina Ligett
2020 A conf
A New Analysis of Differential Privacy's Generalization Guarantees.
ITCS
Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld
2019 A* conf
A Necessary and Sufficient Stability Notion for Adaptive Generalization.
NeurIPS
Moshe Shenfeld, Katrina Ligett
2019 J jnl
A New Analysis of Differential Privacy's Generalization Guarantees.
CoRR
Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld
2019 J jnl
A necessary and sufficient stability notion for adaptive generalization.
CoRR
Katrina Ligett, Moshe Shenfeld