James E. Johndrow

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 23 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it; #8,059 of 35,345 by trust here, #13,962 by citations
• AI Ethics, Fairness & Society — 12 citations into it; #105 of 494 by trust here, #228 by citations
• Safety, Robustness & Interpretability — 12 citations into it
• Sociology and Political Science — 12 citations into it; #2,807 of 22,756 by trust here, #6,353 by citations
• Safety Research — 8 citations into it; #624 of 5,829 by trust here, #1,540 by citations
• Statistics and Probability — 5 citations into it

Whom James E. Johndrow trusts overall

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

1. Kevin A. Clarke
2. Faisal Kamiran
3. Jerome P. Reiter
4. Toon Calders
5. S. van Buuren
6. M. Hoffman
7. Ian R. White
8. Amir Ehsan Khandani
9. Michael Feldman
10. Cynthia Dwork

Who trusts James E. Johndrow overall

1. Luca Oneto
2. Alexandre Louis Lamy
3. Eun Seo Jo
4. Silvia Chiappa
5. Ray Jiang
6. Alexandra Chouldechova
7. Ziyuan Zhong
8. Timnit Gebru
9. Zachary Chase Lipton
10. Shira Mitchell

Papers from James E. Johndrow's perspective

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

1. Classifying without discriminating
2. Fairness through awareness
3. A multidisciplinary survey on discrimination analysis
4. Three naive Bayes approaches for discrimination-free classification
5. Equality of Opportunity in Supervised Learning
6. Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments
7. Certifying and Removing Disparate Impact
8. Big Data's Disparate Impact
9. MICE: Multivariate Imputation by Chained Equations in R
10. Fairness-aware Learning through Regularization Approach

Their papers

• An algorithm for removing sensitive information: Application to race-independent recidivism prediction (2017) — 178 citations
• A statistical framework for fair predictive algorithms (2016) — 114 citations