Pengzhan Wang

Artificial Intelligence · 2016–2019

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it; #29,764 of 35,345 by trust here, #19,018 by citations
• Privacy & Security — 34 citations into it
• Statistics and Probability — 13 citations into it
• Algorithms & Complexity — 7 citations into it

Whom Pengzhan Wang trusts overall

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

1. Robert Tibshirani
2. Jeffrey Scott Vitter
3. Cynthia Dwork
4. John C. Duchi
5. Peter Kairouz
6. Adam D. Smith

Who trusts Pengzhan Wang overall

1. Jayadev Acharya

Papers from Pengzhan Wang's perspective

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

1. Calibrating Noise to Sensitivity in Private Data Analysis
2. Regression Shrinkage and Selection via the Lasso
3. Differential Privacy
4. Randomized response: a survey technique for eliminating evasive answer bias.
5. Robust De-anonymization of Large Sparse Datasets
6. Local Privacy and Statistical Minimax Rates
7. What Can We Learn Privately?
8. RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
9. Extremal Mechanisms for Local Differential Privacy
10. Pseudorandom Bits for Polynomials

Their papers

• Local Differential Private Data Aggregation for Discrete Distribution Estimation (2019) — 81 citations
• Mutual Information Optimally Local Private Discrete Distribution Estimation (2016) — 100 citations