Patricia Egger

Artificial Intelligence · 2017

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 Patricia Egger trusts overall

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

  1. Andrew Neff
  2. Cynthia Dwork
  3. Amos Fiat

Papers from Patricia Egger's perspective

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

  1. Calibrating Noise to Sensitivity in Private Data Analysis
  2. How to Prove Yourself: Practical Solutions to Identification and Signature Problems
  3. Our Data, Ourselves: Privacy Via Distributed Noise Generation
  4. CryptDB: protecting confidentiality with encrypted query processing (Symposium on Operating Systems Principles)
  5. A firm foundation for private data analysis
  6. ObliVM: A Programming Framework for Secure Computation
  7. GraphSC: Parallel Secure Computation Made Easy
  8. Observing and Preventing Leakage in MapReduce
  9. VC3: Trustworthy Data Analytics in the Cloud Using SGX
  10. Efficient Garbling from a Fixed-Key Blockcipher

Their papers