Daniel Noble

Artificial Intelligence · 2019

A researcher in the Science corpus: 2 papers; trusts 35 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 86 citations into it
• Privacy & Security — 45 citations into it
• Computational Theory and Mathematics — 32 citations into it
• Information Systems — 13 citations into it
• Computer Networks and Communications — 8 citations into it
• Electrical and Electronic Engineering — 8 citations into it
• Federated & Distributed Learning — 6 citations into it

Whom Daniel Noble trusts overall

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

1. Cynthia Dwork
2. Frank McSherry
3. Xiao Shaun Wang
4. Johannes Blömer
5. Ivan Bjerre Damgård
6. Pascal Paillier
7. Donald Beaver
8. Craig Gentry
9. Aaron Roth
10. Yehuda Lindell

Papers from Daniel Noble's perspective

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

1. Fair exchange with a semi-trusted third party (extended abstract)
2. Calibrating Noise to Sensitivity in Private Data Analysis
3. Fully homomorphic encryption using ideal lattices
4. How to play ANY mental game
5. How to share a secret
6. Public-Key Cryptosystems Based on Composite Degree Residuosity Classes
7. FairplayMP: a system for secure multi-party computation
8. Boosting and Differential Privacy
9. The Algorithmic Foundations of Differential Privacy
10. Improved Garbled Circuit: Free XOR Gates and Applications

Their papers

• SoK: General Purpose Compilers for Secure Multi-Party Computation (2019) — 186 citations
• Honeycrisp: large-scale differentially private aggregation without a trusted core (2019) — 74 citations