Ge Yu

Artificial Intelligence · 2012–2019

A researcher in the Science corpus: 3 papers; trusts 13 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 74 citations into it; #25,153 of 35,345 by trust here, #14,438 by citations
• Privacy & Security — 48 citations into it
• Statistics and Probability — 21 citations into it
• Computer Science Applications — 18 citations into it
• Management Science and Operations Research — 7 citations into it

Whom Ge Yu trusts overall

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

1. Cynthia Dwork
2. Frank McSherry
3. John C. Duchi

Who trusts Ge Yu overall

1. Ashwin Machanavajjhala
2. Staal Amund Vinterbo
3. Michael Hay

Papers from Ge Yu's perspective

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

1. Calibrating Noise to Sensitivity in Private Data Analysis
2. Randomized response: a survey technique for eliminating evasive answer bias.
3. Boosting and Differential Privacy
4. RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
5. Privacy integrated queries: an extensible platform for privacy-preserving data analysis
6. The Algorithmic Foundations of Differential Privacy
7. Pseudorandom Bits for Polynomials
8. Local Privacy and Statistical Minimax Rates
9. Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays
10. Differential privacy via wavelet transforms

Their papers

• Collecting and Analyzing Multidimensional Data with Local Differential Privacy (2019) — 394 citations
• PrivTrie: Effective Frequent Term Discovery under Local Differential Privacy (2018) — 86 citations
• Differentially private histogram publication (2012) — 344 citations