| 2022 | ICML | Transfer Learning In Differential Privacy's Hybrid-Model. | Refael Kohen, Or Sheffet |
| 2020 | AISTATS | Private k-Means Clustering with Stability Assumptions. | Moshe Shechner, Or Sheffet, Uri Stemmer |
| 2020 | ITA | Differentially Private Algorithms for Learning Mixtures of Separated Gaussians. | Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan R. Ullman |
| 2019 | AISTATS | Locally Private Mean Estimation: $Z$-test and Tight Confidence Intervals. | Marco Gaboardi, Ryan Rogers, Or Sheffet |
| 2019 | ALT | Old Techniques in Differentially Private Linear Regression. | Or Sheffet |
| 2019 | ICML | An Optimal Private Stochastic-MAB Algorithm based on Optimal Private Stopping Rule. | Touqir Sajed, Or Sheffet |
| 2018 | ICML | Locally Private Hypothesis Testing. | Or Sheffet |
| 2017 | ICML | Differentially Private Ordinary Least Squares. | Or Sheffet |
| 2012 | FOCS | The Johnson-Lindenstrauss Transform Itself Preserves Differential Privacy. | Jeremiah Blocki, Avrim Blum, Anupam Datta, Or Sheffet |
| 2012 | ICML | Predicting Consumer Behavior in Commerce Search. | Or Sheffet, Nina Mishra, Samuel Ieong |
| 2010 | COLT | Improved Guarantees for Agnostic Learning of Disjunctions. | Pranjal Awasthi, Avrim Blum, Or Sheffet |
| 2010 | FOCS | Stability Yields a PTAS for k-Median and k-Means Clustering. | Pranjal Awasthi, Avrim Blum, Or Sheffet |
| 2010 | SAGT | On Nash-Equilibria of Approximation-Stable Games. | Pranjal Awasthi, Maria-Florina Balcan, Avrim Blum, Or Sheffet, Santosh S. Vempala |