Sofya Raskhodnikova
Artificial Intelligence · 1996–2013
A researcher in the Science corpus: 7 papers; trusts 16 researchers and is trusted by 193 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 49 citations into it; #1,269 of 35,345 by trust here, #1,799 by citations
- Privacy & Security — 26 citations into it; #19 of 709 by trust here, #19 by citations
- Sociology and Political Science — 12 citations into it
- Computational Theory and Mathematics — 11 citations into it; #5,153 of 12,182 by trust here, #1,851 by citations
- Statistics and Probability — 10 citations into it; #595 of 12,932 by trust here, #615 by citations
- Safety, Robustness & Interpretability — 7 citations into it; #321 of 2,251 by trust here, #275 by citations
- Management Science and Operations Research — 6 citations into it
- Electrical and Electronic Engineering — 5 citations into it; #190 of 16,539 by trust here, #2,550 by citations
Whom Sofya Raskhodnikova trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Cynthia Dwork
- Frank McSherry
- Kobbi Nissim
- Adam D. Smith
- Michael Hay
- Avrim Blum
- Latanya Sweeney
- Irit Dinur
- Vibhor Rastogi
- Ilya Mironov
Who trusts Sofya Raskhodnikova overall
- Adam D. Smith
- Kamalika Chaudhuri
- Cynthia Dwork
- Ashwin Machanavajjhala
- Abhradeep Thakurta
- Mark Bun
- Daniel Kifer
- Shiva Prasad Kasiviswanathan
- Kobbi Nissim
- Ilya Mironov
Papers from Sofya Raskhodnikova's perspective
Ordered by how strongly the researchers Sofya Raskhodnikova trusts endorse each paper. Same corpus, a different order for every researcher.
- Revealing information while preserving privacy
- Calibrating Noise to Sensitivity in Private Data Analysis
- Differentially private recommender systems: building privacy into the net
- Differential Privacy
- Privacy, accuracy, and consistency too: a holistic solution to contingency table release
- Toward Privacy in Public Databases
- Smooth sensitivity and sampling in private data analysis
- Security-control methods for statistical databases: a comparative study
- Relationship privacy: output perturbation for queries with joins
- Accurate Estimation of the Degree Distribution of Private Networks
Their papers
- What Can We Learn Privately? (2008) — 1,627 citations
- Smooth sensitivity and sampling in private data analysis (2007) — 1,280 citations
- Private analysis of graph structure (2011) — 308 citations
- Strong Lower Bounds for Approximating Distribution Support Size and the Distinct Elements Problem (2007) — 147 citations
- Analyzing Graphs with Node Differential Privacy (2013) — 425 citations
- Testing the Lipschitz Property over Product Distributions with Applications to Data Privacy (2013) — 29 citations
- in Computing (1996)