Shay Moran

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it; #26,740 of 35,345 by trust here, #32,362 by citations
• Privacy & Security — 15 citations into it
• Statistical Learning Theory — 6 citations into it

Whom Shay Moran trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Cynthia Dwork
2. Vladimir Naumovich Vapnik
3. Frank McSherry
4. Kobbi Nissim
5. Amos Beimel
6. Nick Littlestone
7. Shai Shalev-Shwartz
8. Moritz Hardt
9. Guy N. Rothblum

Who trusts Shay Moran overall

1. Yingxue Zhou

Papers from Shay Moran's perspective

Ordered by how strongly the researchers Shay Moran trusts endorse each paper. Same corpus, a different order for every researcher.

1. Calibrating Noise to Sensitivity in Private Data Analysis
2. Revealing information while preserving privacy
3. Boosting and Differential Privacy
4. Understanding Machine Learning - From Theory to Algorithms
5. Pseudorandom Bits for Polynomials
6. Differentially Private Release and Learning of Threshold Functions
7. Chervonenkis: On the uniform convergence of relative frequencies of events to their probabilities
8. The Algorithmic Foundations of Differential Privacy
9. Scalable Private Learning with PATE
10. Optimal private halfspace counting via discrepancy

Their papers

• Limits of Private Learning with Access to Public Data (2019) — 58 citations
• Private Query Release Assisted by Public Data (2020) — 53 citations