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2020 – today
- 2022
[c27]Refael Kohen, Or Sheffet:
Transfer Learning In Differential Privacy's Hybrid-Model. ICML 2022: 11413-11429- [c26]Bar Mahpud, Or Sheffet:
A Differentially Private Linear-Time fPTAS for the Minimum Enclosing Ball Problem. NeurIPS 2022 - [i22]Refael Kohen, Or Sheffet:
Transfer Learning In Differential Privacy's Hybrid-Model. CoRR abs/2201.12018 (2022) - [i21]Bar Mahpud, Or Sheffet:
A Differentially Private Linear-Time fPTAS for the Minimum Enclosing Ball Problem. CoRR abs/2206.03319 (2022) - 2021
- [j8]Konstantinos E. Nikolakakis
, Dionysios S. Kalogerias, Or Sheffet, Anand D. Sarwate:
Quantile Multi-Armed Bandits: Optimal Best-Arm Identification and a Differentially Private Scheme. IEEE J. Sel. Areas Inf. Theory 2(2): 534-548 (2021) - [c25]Yue Gao, Or Sheffet:
Differentially Private Approximations of a Convex Hull in Low Dimensions. ITC 2021: 18:1-18:16 - 2020
- [j7]Yiling Chen, Or Sheffet, Salil P. Vadhan:
Privacy Games. ACM Trans. Economics and Comput. 8(2): 9:1-9:37 (2020) - [c24]Moshe Shechner, Or Sheffet, Uri Stemmer:
Private k-Means Clustering with Stability Assumptions. AISTATS 2020: 2518-2528 - [c23]Amos Beimel, Aleksandra Korolova, Kobbi Nissim, Or Sheffet, Uri Stemmer:
The Power of Synergy in Differential Privacy: Combining a Small Curator with Local Randomizers. ITC 2020: 14:1-14:25 - [c22]Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan R. Ullman:
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians. ITA 2020: 1-62 - [i20]Dionysios S. Kalogerias, Konstantinos E. Nikolakakis, Anand D. Sarwate, Or Sheffet:
Best-Arm Identification for Quantile Bandits with Privacy. CoRR abs/2006.06792 (2020) - [i19]Yue Gao, Or Sheffet:
Private Approximations of a Convex Hull in Low Dimensions. CoRR abs/2007.08110 (2020)
2010 – 2019
- 2019
- [j6]Or Sheffet:
Differentially Private Ordinary Least Squares. J. Priv. Confidentiality 9(1) (2019) - [c21]Marco Gaboardi, Ryan Rogers, Or Sheffet:
Locally Private Mean Estimation: $Z$-test and Tight Confidence Intervals. AISTATS 2019: 2545-2554 - [c20]Or Sheffet:
Old Techniques in Differentially Private Linear Regression. ALT 2019: 788-826 - [c19]Touqir Sajed, Or Sheffet:
An Optimal Private Stochastic-MAB Algorithm based on Optimal Private Stopping Rule. ICML 2019: 5579-5588 - [c18]Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan R. Ullman:
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians. NeurIPS 2019: 168-180 - [i18]Touqir Sajed, Or Sheffet:
An Optimal Private Stochastic-MAB Algorithm Based on an Optimal Private Stopping Rule. CoRR abs/1905.09383 (2019) - [i17]Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan R. Ullman:
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians. CoRR abs/1909.03951 (2019) - [i16]Amos Beimel, Aleksandra Korolova, Kobbi Nissim, Or Sheffet, Uri Stemmer:
The power of synergy in differential privacy: Combining a small curator with local randomizers. CoRR abs/1912.08951 (2019) - 2018
- [c17]Or Sheffet:
Locally Private Hypothesis Testing. ICML 2018: 4612-4621 - [c16]Roshan Shariff, Or Sheffet:
Differentially Private Contextual Linear Bandits. NeurIPS 2018: 4301-4311 - [i15]Or Sheffet:
Locally Private Hypothesis Testing. CoRR abs/1802.03441 (2018) - [i14]Roshan Shariff, Or Sheffet:
Differentially Private Contextual Linear Bandits. CoRR abs/1810.00068 (2018) - [i13]Marco Gaboardi, Ryan Rogers, Or Sheffet:
Locally Private Mean Estimation: Z-test and Tight Confidence Intervals. CoRR abs/1810.08054 (2018) - 2017
- [c15]Or Sheffet:
Differentially Private Ordinary Least Squares. ICML 2017: 3105-3114 - 2015
- [j5]Craig Boutilier, Ioannis Caragiannis, Simi Haber, Tyler Lu, Ariel D. Procaccia, Or Sheffet:
Optimal social choice functions: A utilitarian view. Artif. Intell. 227: 190-213 (2015) - [i12]Or Sheffet:
Private Approximations of the 2nd-Moment Matrix Using Existing Techniques in Linear Regression. CoRR abs/1507.00056 (2015) - [i11]Or Sheffet:
Differentially Private Least Squares: Estimation, Confidence and Rejecting the Null Hypothesis. CoRR abs/1507.02482 (2015) - 2014
- [c14]Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan:
Learning Mixtures of Ranking Models. NIPS 2014: 2609-2617 - [c13]Yiling Chen, Or Sheffet, Salil P. Vadhan:
Privacy Games. WINE 2014: 371-385 - [i10]Yiling Chen, Or Sheffet, Salil P. Vadhan:
Privacy Games. CoRR abs/1410.1920 (2014) - [i9]Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan:
Learning Mixtures of Ranking Models. CoRR abs/1410.8750 (2014) - 2013
- [c12]Jeremiah Blocki, Avrim Blum, Anupam Datta, Or Sheffet:
Differentially private data analysis of social networks via restricted sensitivity. ITCS 2013: 87-96 - [c11]Jeremiah Blocki, Saranga Komanduri, Ariel D. Procaccia, Or Sheffet:
Optimizing password composition policies. EC 2013: 105-122 - [i8]Jeremiah Blocki, Saranga Komanduri, Ariel D. Procaccia, Or Sheffet:
Optimizing Password Composition Policies. CoRR abs/1302.5101 (2013) - 2012
- [j4]Pranjal Awasthi, Avrim Blum, Or Sheffet:
Center-based clustering under perturbation stability. Inf. Process. Lett. 112(1-2): 49-54 (2012) - [c10]Pranjal Awasthi, Avrim Blum, Jamie Morgenstern, Or Sheffet:
Additive Approximation for Near-Perfect Phylogeny Construction. APPROX-RANDOM 2012: 25-36 - [c9]Pranjal Awasthi, Or Sheffet:
Improved Spectral-Norm Bounds for Clustering. APPROX-RANDOM 2012: 37-49 - [c8]Jeremiah Blocki, Avrim Blum, Anupam Datta, Or Sheffet:
The Johnson-Lindenstrauss Transform Itself Preserves Differential Privacy. FOCS 2012: 410-419 - [c7]Or Sheffet, Nina Mishra, Samuel Ieong:
Predicting Consumer Behavior in Commerce Search. ICML 2012 - [c6]Craig Boutilier, Ioannis Caragiannis, Simi Haber, Tyler Lu, Ariel D. Procaccia, Or Sheffet:
Optimal social choice functions: a utilitarian view. EC 2012: 197-214 - [c5]Peter Bro Miltersen, Or Sheffet:
Send mixed signals: earn more, work less. EC 2012: 234-247 - [i7]Peter Bro Miltersen, Or Sheffet:
Send Mixed Signals -- Earn More, Work Less. CoRR abs/1202.1483 (2012) - [i6]Jeremiah Blocki, Avrim Blum, Anupam Datta, Or Sheffet:
The Johnson-Lindenstrauss Transform Itself Preserves Differential Privacy. CoRR abs/1204.2136 (2012) - [i5]Pranjal Awasthi, Or Sheffet:
Improved Spectral-Norm Bounds for Clustering. CoRR abs/1206.3204 (2012) - [i4]Pranjal Awasthi, Avrim Blum, Jamie Morgenstern, Or Sheffet:
Additive Approximation for Near-Perfect Phylogeny Construction. CoRR abs/1206.3334 (2012) - [i3]Jeremiah Blocki, Avrim Blum, Anupam Datta, Or Sheffet:
Differentially Private Data Analysis of Social Networks via Restricted Sensitivity. CoRR abs/1208.4586 (2012) - 2010
- [j3]Oded Goldreich, Or Sheffet:
On The Randomness Complexity of Property Testing. Comput. Complex. 19(1): 99-133 (2010) - [c4]Pranjal Awasthi, Avrim Blum, Or Sheffet:
Improved Guarantees for Agnostic Learning of Disjunctions. COLT 2010: 359-367 - [c3]Pranjal Awasthi, Avrim Blum, Or Sheffet:
Stability Yields a PTAS for k-Median and k-Means Clustering. FOCS 2010: 309-318 - [c2]Pranjal Awasthi, Maria-Florina Balcan, Avrim Blum, Or Sheffet, Santosh S. Vempala:
On Nash-Equilibria of Approximation-Stable Games. SAGT 2010: 78-89 - [i2]Pranjal Awasthi, Avrim Blum, Or Sheffet:
Center-based Clustering under Perturbation Stability. CoRR abs/1009.3594 (2010)
2000 – 2009
- 2008
- [j2]Nathan Linial, Jirí Matousek, Or Sheffet, Gábor Tardos:
Graph Colouring with No Large Monochromatic Components. Comb. Probab. Comput. 17(4): 577-589 (2008) - 2007
- [j1]Nathan Linial, Jirí Matousek, Or Sheffet, Gábor Tardos:
Graph coloring with no large monochromatic components. Electron. Notes Discret. Math. 29: 115-122 (2007) - [c1]Oded Goldreich, Or Sheffet:
On the Randomness Complexity of Property Testing. APPROX-RANDOM 2007: 509-524 - [i1]Oded Goldreich, Or Sheffet:
On the randomness complexity of property testing. Electron. Colloquium Comput. Complex. TR07 (2007)
Coauthor Index
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