Seunghyun Lee

Artificial Intelligence · with Ahammad · 2020

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

Subfields

Whom Seunghyun Lee trusts overall

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

  1. Frank McSherry

Papers from Seunghyun Lee's perspective

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

  1. RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
  2. Calibrating Noise to Sensitivity in Private Data Analysis
  3. Privacy integrated queries: an extensible platform for privacy-preserving data analysis
  4. Deep Learning with Differential Privacy
  5. Pseudorandom Bits for Polynomials
  6. Collecting Telemetry Data Privately
  7. Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds
  8. Privacy integrated queries
  9. The Composition Theorem for Differential Privacy
  10. PSI (Ψ): a Private data Sharing Interface

Their papers