Junbum Shin

Artificial Intelligence · 2016–2019

A researcher in the Science corpus: 3 papers; trusts 15 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 66 citations into it; #25,003 of 35,345 by trust here, #16,771 by citations
• Privacy & Security — 45 citations into it
• Statistics and Probability — 20 citations into it
• Computer Science Applications — 18 citations into it; #1,580 of 1,855 by trust here, #941 by citations
• Algorithms & Complexity — 13 citations into it
• Management Science and Operations Research — 5 citations into it
• Safety, Robustness & Interpretability — 5 citations into it

Whom Junbum Shin trusts overall

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

1. John C. Duchi
2. Cynthia Dwork
3. Frank McSherry
4. Ú. Erlingsson
5. Michael I. Jordan
6. Raef Bassily

Who trusts Junbum Shin overall

1. Tianhao Wang

Papers from Junbum Shin's perspective

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

1. Calibrating Noise to Sensitivity in Private Data Analysis
2. Revealing information while preserving privacy
3. Randomized response: a survey technique for eliminating evasive answer bias.
4. RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
5. Et al
6. The Algorithmic Foundations of Differential Privacy
7. Pseudorandom Bits for Polynomials
8. Privacy-Preserving Datamining on Vertically Partitioned Databases
9. Support-Vector Networks
10. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper

Their papers

• Collecting and Analyzing Multidimensional Data with Local Differential Privacy (2019) — 394 citations
• PrivTrie: Effective Frequent Term Discovery under Local Differential Privacy (2018) — 86 citations
• Collecting and Analyzing Data from Smart Device Users with Local Differential Privacy (2016) — 215 citations