activity
20202026
most citedDiversity and Inclusion Metrics in Subset Selection

66 citations · 84 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CY2026★ 6 cited

From experimentation to engagement: on the paradox of participatory AI and power in contexts of forced displacement and humanitarian crises

Stella Suge, Sarah W. Spencer, Nyalleng Moorosi +3

Across the Global North, calls for participatory artificial intelligence (AI) to improve the responsible, safe, and ethical use of AI have increased, particularly efforts that enga…

cs.LG2023★ 1 cited

Length of Stay prediction for Hospital Management using Domain Adaptation

Lyse Naomi Wamba Momo, Nyalleng Moorosi, Elaine O. Nsoesie +2

Inpatient length of stay (LoS) is an important managerial metric which if known in advance can be used to efficiently plan admissions, allocate resources and improve care. Using hi…

cs.AI2022★ 9 cited

Healthsheet: Development of a Transparency Artifact for Health Datasets

Negar Rostamzadeh, Diana Mincu, Subhrajit Roy +7

Machine learning (ML) approaches have demonstrated promising results in a wide range of healthcare applications. Data plays a crucial role in developing ML-based healthcare systems…

stat.ML2022★ 2 cited

Fair Wrapping for Black-box Predictions

Alexander Soen, Ibrahim Alabdulmohsin, Sanmi Koyejo +5

We introduce a new family of techniques to post-process ("wrap") a black-box classifier in order to reduce its bias. Our technique builds on the recent analysis of improper loss fu…

cs.AI2020

Fairness Preferences, Actual and Hypothetical: A Study of Crowdworker Incentives

Angie Peng, Jeff Naecker, Ben Hutchinson +2

How should we decide which fairness criteria or definitions to adopt in machine learning systems? To answer this question, we must study the fairness preferences of actual users of…

cs.LG2020

Characterising Bias in Compressed Models

Sara Hooker, Nyalleng Moorosi, Gregory Clark +2

The popularity and widespread use of pruning and quantization is driven by the severe resource constraints of deploying deep neural networks to environments with strict latency, me…