Shahin Jabbari

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 4 papers; trusts 23 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 80 citations into it
• Safety Research — 44 citations into it; #3,910 of 5,829 by trust here, #923 by citations
• AI Ethics, Fairness & Society — 42 citations into it; #374 of 494 by trust here, #91 by citations
• Safety, Robustness & Interpretability — 42 citations into it; #1,296 of 2,251 by trust here, #705 by citations
• Sociology and Political Science — 30 citations into it; #10,077 of 22,756 by trust here, #2,752 by citations
• Statistics and Probability — 16 citations into it
• Reinforcement Learning — 11 citations into it
• Statistical Learning Theory — 8 citations into it

Whom Shahin Jabbari trusts overall

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

1. Richard A. Berk
2. Michael Kearns
3. Faisal Kamiran
4. Moritz Hardt
5. Matthew Joseph
6. Sara Hajian
7. Toon Calders
8. Toshihiro Kamishima
9. Latanya Sweeney
10. Trevor J. Hastie

Who trusts Shahin Jabbari overall

1. Dana Pessach
2. Michael Kearns
3. Erez Shmueli
4. Aaron Roth
5. Tatsunori B. Hashimoto
6. Alexandra Chouldechova
7. Luca Oneto
8. Simon Caton
9. Sam Corbett-Davies
10. A. D'Amour

Papers from Shahin Jabbari's perspective

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

1. Fairness through awareness
2. Equality of Opportunity in Supervised Learning
3. Discrimination-aware data mining
4. Fairness-Aware Classifier with Prejudice Remover Regularizer
5. Fairness-aware Learning through Regularization Approach
6. Certifying and Removing Disparate Impact
7. Three naive Bayes approaches for discrimination-free classification
8. ImageNet classification with deep convolutional neural networks
9. Big Data's Disparate Impact
10. Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments

Their papers

• Fairness in Reinforcement Learning (2016) — 234 citations
• Fairness in Criminal Justice Risk Assessments: The State of the Art (2017) — 1,137 citations
• A Convex Framework for Fair Regression (2017) — 379 citations
• Fair Learning in Markovian Environments (2016) — 35 citations