Kaiyan Shi

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Kaiyan Shi trusts overall

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

  1. Marco Gaboardi
  2. Cynthia Dwork
  3. Adam D. Smith

Papers from Kaiyan Shi's perspective

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

  1. Calibrating Noise to Sensitivity in Private Data Analysis
  2. Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays
  3. Differential Privacy for Clinical Trial Data: Preliminary Evaluations
  4. Privacy-Preserving Data Exploration in Genome-Wide Association Studies
  5. A Statistical Framework for Differential Privacy
  6. Smooth sensitivity and sampling in private data analysis
  7. Privacy-Preserving Data Sharing for Genome-Wide Association Studies
  8. Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing
  9. Efficient, Differentially Private Point Estimators
  10. Our Data, Ourselves: Privacy Via Distributed Noise Generation

Their papers