Or Sheffet
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- Auction Theory and Applications 5
- Game Theory and Applications 3
- Artificial Intelligence top 5%
- Privacy-Preserving Technologies in Data 8
- Cryptography and Data Security 6
- Machine Learning and Algorithms 3
- Bayesian Modeling and Causal Inference 2
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- Complexity and Algorithms in Graphs 6
- Economics and Econometrics top 10%
- Game Theory and Voting Systems 3
- Co-authors
- Avrim BlumJeremiah BlockiAnupam DattaPranjal AwasthiAriel D. ProcacciaTyler LuIoannis CaragiannisCraig Boutilier
- Cited by
- Management Science and Operations ResearchComputer Science ApplicationsArtificial Intelligence
- Journals
- Artificial Intelligence (1 paper)Combinatorics Probability Computing (1 paper)Computational Complexity (1 paper)
- Partner nations
- United StatesCanadaIsrael
In The Last Decade
Or Sheffet
24 papers receiving 473 citations
Peers
Comparison fields: 5 of 59
- Management Science and Operations Research 151
- Computer Science Applications 58
- Artificial Intelligence 285
- Computational Theory and Mathematics 95
- Economics and Econometrics 125
Countries citing papers authored by Or Sheffet
This map shows the geographic impact of Or Sheffet's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Or Sheffet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Or Sheffet more than expected).
Fields of papers citing papers by Or Sheffet
This network shows the impact of papers produced by Or Sheffet. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Or Sheffet. The network helps show where Or Sheffet may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Or Sheffet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 1 | |
| 2 | Private k-Means Clustering with Stability Assumptions. | 2020 | 2 |
| 3 | Old Techniques in Differentially Private Linear Regression. | 2019 | 3 |
| 4 | 2019 | 3 | |
| 5 | Differentially Private Contextual Linear Bandits | 2018 | 8 |
| 6 | 2018 | 2 | |
| 7 | 2018 | 9 | |
| 8 | 2018 | 0 | |
| 9 | Differentially Private Least Squares: Estimation, Confidence and Rejecting the Null Hypothesis. | 2015 | 5 |
| 10 | 2015 | 70 | |
| 11 | 2014 | 13 | |
| 12 | 2013 | 102 | |
| 13 | Beyond Worst-Case Analysis in Privacy and Clustering: Exploiting Explicit and Implicit Assumptions | 2013 | 1 |
| 14 | Predicting Consumer Behavior in Commerce Search. | 2012 | 4 |
| 15 | 2012 | 69 | |
| 16 | 2012 | 34 | |
| 17 | 2011 | 45 | |
| 18 | 2010 | 3 | |
| 19 | 2010 | 34 | |
| 20 | 2007 | 5 |
About Or Sheffet
Or Sheffet is a scholar working on Computer Graphics and Computer-Aided Design, Computational Theory and Mathematics and Management Science and Operations Research, having authored 25 papers that have together received 498 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (8 papers), Cryptography and Data Security (6 papers), Complexity and Algorithms in Graphs (6 papers), Auction Theory and Applications (5 papers), Game Theory and Applications (3 papers), Machine Learning and Algorithms (3 papers), Game Theory and Voting Systems (3 papers) and Bayesian Modeling and Causal Inference (2 papers). The work is most often cited by research in Management Science and Operations Research (151 citations), Computer Science Applications (58 citations) and Artificial Intelligence (285 citations). Or Sheffet has collaborated with scholars based in United States, Canada and Israel. Frequent co-authors include Avrim Blum, Jeremiah Blocki, Anupam Datta, Pranjal Awasthi, Ariel D. Procaccia, Tyler Lu, Ioannis Caragiannis, Craig Boutilier, Simi Haber and Peter Bro Miltersen. Their work appears in journals such as Artificial Intelligence, Combinatorics Probability Computing, Computational Complexity, Information Processing Letters and Electronic Notes in Discrete Mathematics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.