Mukul Kulkarni

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Computational Theory and Mathematics — 13 citations into it
• Privacy & Security — 13 citations into it

Whom Mukul Kulkarni trusts overall

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

1. Cynthia Dwork
2. Tamás Sarlós
3. Nir Ailon
4. Sariel Har-Peled
5. William B. Johnson

Papers from Mukul Kulkarni's perspective

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

1. Calibrating Noise to Sensitivity in Private Data Analysis
2. Approximate Nearest Neighbor: Towards Removing the Curse of Dimensionality
3. Secure multiparty computation of approximations
4. An improved data stream summary: the count-min sketch and its applications
5. Extensions of Lipschitz mappings into Hilbert space
6. Counting Distinct Elements in a Data Stream (International Workshop Randomization and Approximation Techniques in Computer Science)
7. Towards Sharp Inapproximability For Any 2-CSP
8. The Fast Johnson--Lindenstrauss Transform and Approximate Nearest Neighbors
9. Finding frequent items in data streams
10. The Algorithmic Foundations of Differential Privacy

Their papers

• Differentially-Private Multi-Party Sketching for Large-Scale Statistics (2020) — 39 citations