Brian Thorne

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it; #24,966 of 35,345 by trust here, #10,798 by citations
• Privacy & Security — 13 citations into it; #603 of 709 by trust here, #342 by citations
• Management Science and Operations Research — 12 citations into it
• Algorithms & Complexity — 7 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Brian Thorne trusts overall

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

1. Peter Christen
2. Pascal Paillier
3. R. Schnell
4. Richard Nock
5. Giorgio Patrini

Who trusts Brian Thorne overall

1. Qiang Yang
2. Yang Liu
3. Tianjian Chen

Papers from Brian Thorne's perspective

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

1. Differential Privacy: A Survey of Results
2. A Constraint Satisfaction Cryptanalysis of Bloom Filters in Private Record Linkage
3. Convexity, Classification, and Risk Bounds
4. Minimizing finite sums with the stochastic average gradient
5. Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
6. Fair exchange with a semi-trusted third party (extended abstract)
7. Matrix analysis
8. A Novel Error-Tolerant Anonymous Linking Code
9. The Hungarian method for the assignment problem
10. Public-Key Cryptosystems Based on Composite Degree Residuosity Classes

Their papers

• Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption (2017) — 622 citations
• Entity Resolution and Federated Learning get a Federated Resolution (2018) — 95 citations
• Privacy-preserving entity resolution and logistic regression on encrypted data (2017)