Students

List of past and current advisees

• Bar Mahpud (MEng, 2020-)
• Refael Kohen (MEng, 2019-)
• Yue (Anna) Gao (MSc, 2018-21)
• Touqir Sajed (MSc, 2017-9)

If you think you might be interested in working with me, please read my

• (rather long) advice for a General CS/Eng Students, about applications, expectations, the life of a grad student and the importance of choosing the best advisor for you. (Written while at University of Alberta)
• (shorter) advice for anyone considering me as an advisor, regarding my field of research, my expectations from students, and how to contact me.

Publications

• Private Approximations of a Convex Hull in Low Dimensions, Yue Gao and Or Sheffet, ITC 2021.
  Paper.
  
  
• Quantile Multi-Armed Bandits: Optimal Best-Arm Identification and a Differentially Private Scheme, Konstantinos Nikolakakis, Dionysios Kalogerias, Or Sheffet and Anand Sarwate, IEEE Journal on Selected Areas in Information Theory, Vol. 2 No. 2. 2021.
  Paper.
  
  
• The Power of Synergy in Differential Privacy: Combining a Small Curator with Local Randomizers, Amos Beimel, Aleksandra Korolova, Kobbi Nissim, Or Sheffet and Uri Stemmer, ITC 2020.
  Paper.
  
  
• Private k-Means Clustering with Stability Assumptions, Moshe Shechner, Or Sheffet, Uri Stemmer, AISTATS 2020.
  Paper.
  
  
• Differentially Private Algorithms for Learning Mixtures of Separated Gaussians, Gautam Kamath, Or Sheffet, Vikrant Singhal and Jonathan Ullman, NeurIPS 2019.
  Paper.
  
  
• Locally Private Confidence Intervals: Z-test and Tight Confidence Intervals, Marco Gaboardi, Ryan Rogers and Or Sheffet, AISTATS 2019.
  Paper.
  
  
• Old Techniques In Private Linear Regression, Or Sheffet, ALT 2019.
  (Based on “Private Approximations of the 2nd-Moment Matrix Using Existing Techniques in Linear Regression” in NIPS 2015 Workshop on Learning and Privacy.)
  Paper.
  
  
• Differentially Private Contextual Linear Bandits, Roshan Shariff and Or Sheffet, NIPS 2018.
  Paper.
  
  
• Locally Private Hypothesis Testing, Or Sheffet, ICML 2018.
  Paper.
  
  
• Differentially Private Ordinary Least Squares, Or Sheffet, ICML 2017.
  (Based on “Differentially Private Ordinary Least Squares: t-Values, Confidence Intervals and Rejecting Null-Hypotheses” in TPDP 2016.)
  Paper.
  
  
• Privacy Games, Yiling Chen, Or Sheffet and Salil Vadhan, WINE 2014 & ACM Transaction on Economics and Computation (TEAC), Vol. 8 No.2,
  Paper.
  
  
• Learning Mixture of Ranking Models, Pranjal Awasthi, Avrim Blum, Or Sheffet and Aravindan Vijayaraghavan, NIPS 2014.
  Paper.
  Based on “Learning Mixture of Mallows Models”, in Workship on Spectral Learning, NIPS 2013.
  
  
• Optimizing Password Composition Policies, Jeremiah Blocki, Saranga Komanduri, Ariel Procaccia and Or Sheffet, EC 2013.
  Paper.
  
  
• Differentially Private Analysis of Social Networks via Restricted Sensitivity, Jeremiah Blocki, Avrim Blum, Anupam Datta and Or Sheffet, ITCS 2013.
  Paper.
  
  
• The Johnson-Lindenstrauss Transform Itself Preserves Differential Privacy, Jeremiah Blocki, Avrim Blum, Anupam Datta and Or Sheffet, FOCS 2012.
  Paper.
  
  
• Additive Approximation for Near-Perfect Phylogeny Construction, Pranjal Awasthi, Avrim Blum, Jamie Morgenstern and Or Sheffet, APPROX-RANDOM 2012.
  Paper.
  
  
• Improved Spectral Norm Bounds for Clustering, Pranjal Awasthi and Or Sheffet, APPROX-RANDOM 2012.
  Paper.
  
  
• Predicting Preference Flips in Commerce Search, Samuel Ieong, Nina Mishra and Or Sheffet, ICML 2012.
  Paper.
  
  
• Optimal Choice Functions: A Utilitarian View, Craig Boutilier, Ioannis Caragiannis, Simi Haber, Tyler Lu, Ariel Procaccia and Or Sheffet, EC 2012.
  Paper.
  
  
• Send Mixed Signals ‒ Earn More, Work Less, Peter Bro Miltersen and Or Sheffet, EC 2012.
  Paper.
  
  
• Center-based Clustering under Perturbation Stability, Pranjal Awasthi, Avrim Blum and Or Sheffet, Information Processing Letters, 112(1-2).
  Paper.
  
  
• Stability Yields a PTAS for k-Median and k-Means, Pranjal Awasthi, Avrim Blum and Or Sheffet, FOCS 2010.
  Paper.
  
  
• On Nash-Eqilibria of Approximation-Stable Games, Pranjal Awasthi, Nina Balcan, Avrim Blum, Or Sheffet and Santosh Vempala. SAGT 2010.
  Paper. Journal Version (for general audience).
  
  
• Improved Guarantees for Agnostic Learning of Disjunctions, Pranjal Awasthi, Avrim Blum and Or Sheffet, COLT 2010.
  Paper.
  
  
• On the Randomness Complexity of Property Testing, Oded Goldreich and Or Sheffet, Journal of Computational Complexity 19 (2), 2010. Originally appeared in Approx/Random 2007.
  Oded's page.
  (Based on my M.Sc. thesis: “Reducing the Randomness Complexity of Property Testing, with an Emphasis on Testing Bipartiteness”.)
  
  
• Graph Coloring with No Large Monochromatic Components, Nathan Linial, Jiri Matousek, Or Sheffet and Gabor Tardos, Journal of Combinatorial Theory Series B 17 (4), 2008. Originally appeared in Eurocomb 2007.
  Paper.
  (Based on my “Amirim” Honors program final project: “On Ramsey Type Problems in Graphs, and the Largest Monochromatic Connected Component in a 2-Edge-Coloring of a Graph.”)