Per Austrin

Computational Theory and Mathematics · 2007

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 94 researchers here, as inferred from the citation graph.

Subfields

Whom Per Austrin trusts overall

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

  1. Cynthia Dwork
  2. Kobbi Nissim
  3. Avrim Blum
  4. Frank McSherry
  5. Subhash Khot
  6. Adam D. Smith
  7. Sofya Raskhodnikova
  8. Sanjeev Arora
  9. Noam Nisan
  10. J. Håstad

Who trusts Per Austrin overall

  1. Kamalika Chaudhuri
  2. Frank McSherry
  3. Luca Bonomi
  4. Zhanglong Ji
  5. Cynthia Dwork
  6. Quan Geng
  7. Gergely Ács
  8. Adam D. Smith
  9. Larry A. Wasserman
  10. Aaron Johnson

Papers from Per Austrin's perspective

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

  1. Calibrating Noise to Sensitivity in Private Data Analysis
  2. Practical privacy: the SuLQ framework
  3. Revealing information while preserving privacy
  4. Smooth sensitivity and sampling in private data analysis
  5. Efficient noise-tolerant learning from statistical queries
  6. Differentially private recommender systems: building privacy into the net
  7. Toward Privacy in Public Databases
  8. Privacy, accuracy, and consistency too: a holistic solution to contingency table release
  9. Towards Sharp Inapproximability For Any 2-CSP
  10. Security-control methods for statistical databases: a comparative study

Their papers