Arik Friedman

Artificial Intelligence · 2010–2015

A researcher in the Science corpus: 3 papers; trusts 20 researchers and is trusted by 44 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it; #5,032 of 35,345 by trust here, #11,921 by citations
• Privacy & Security — 18 citations into it
• Sociology and Political Science — 8 citations into it; #1,623 of 22,756 by trust here, #6,224 by citations
• Statistics and Probability — 7 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Safety, Robustness & Interpretability — 6 citations into it
• Information Systems — 5 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Arik Friedman trusts overall

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

1. Cynthia Dwork
2. Frank McSherry
3. J. Ross Quinlan
4. Niko Speybroeck
5. Avrim Blum
6. Pedro M. Domingos
7. Kobbi Nissim
8. Moritz Hardt
9. Kamalika Chaudhuri
10. Adam D. Smith

Who trusts Arik Friedman overall

1. Kamalika Chaudhuri
2. Daniel Kifer
3. Jaewoo Lee
4. Richard Nock
5. Zhanglong Ji
6. Jun Zhang
7. Ashwin Machanavajjhala
8. Michael D. Ekstrand
9. Benjamin Stoddard
10. Tianqing Zhu

Papers from Arik Friedman's perspective

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

1. Differentially private recommender systems: building privacy into the net
2. Calibrating Noise to Sensitivity in Private Data Analysis
3. Differential Privacy
4. Differentially Private Empirical Risk Minimization
5. ImageNet classification with deep convolutional neural networks
6. Practical privacy: the SuLQ framework
7. Boosting and Differential Privacy
8. Induction of decision trees
9. Revealing information while preserving privacy
10. Gradient-based learning applied to document recognition

Their papers

• Data mining with differential privacy (2010) — 524 citations
• Rademacher Observations, Private Data, and Boosting (2015) — 13 citations
• Applying Differential Privacy to Matrix Factorization (2015) — 150 citations