Eric Potash
Artificial Intelligence · 2015–2021
A researcher in the Science corpus: 3 papers; trusts 35 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 70 citations into it
- Safety Research — 61 citations into it
- AI Ethics, Fairness & Society — 53 citations into it
- Safety, Robustness & Interpretability — 53 citations into it
- Sociology and Political Science — 53 citations into it
- Statistics and Probability — 35 citations into it
- Management Science and Operations Research — 15 citations into it
- Evaluation & Benchmarks — 14 citations into it
Whom Eric Potash trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Toon Calders
- Alexandra Chouldechova
- Lily Hu
- Faisal Kamiran
- Sam Corbett-Davies
- Michael Kearns
- Matthew Joseph
- Camelia Simoiu
- Sorelle A. Friedler
- Moritz Hardt
Papers from Eric Potash's perspective
Ordered by how strongly the researchers Eric Potash trusts endorse each paper. Same corpus, a different order for every researcher.
- Fairness through awareness
- ImageNet classification with deep convolutional neural networks
- Equality of Opportunity in Supervised Learning
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Certifying and Removing Disparate Impact
- Inherent Trade-Offs in the Fair Determination of Risk Scores
- Big Data's Disparate Impact
- Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Their papers
- Prediction-Based Decisions and Fairness: A Catalogue of Choices, Assumptions, and Definitions (2018) — 182 citations
- Algorithmic Fairness: Choices, Assumptions, and Definitions (2021) — 600 citations
- Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning (2015) — 52 citations