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Michelle Bao

3 papers hereh-index 3500 citations3 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • last author1

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CY1

identity via Semantic Scholar / OpenAlex

most citedIt's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks

34 citations · 48 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2023

Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift

Benjamin Eyre, Elliot Creager, David Madras +2

Designing deep neural network classifiers that perform robustly on distributions differing from the available training data is an active area of machine learning research. However,…

cs.LG2021★ 14 cited

The Values Encoded in Machine Learning Research

Abeba Birhane, Pratyusha Kalluri, Dallas Card +3

Machine learning currently exerts an outsized influence on the world, increasingly affecting institutional practices and impacted communities. It is therefore critical that we ques…

cs.CY2021★ 34 cited

It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks

Michelle Bao, Angela Zhou, Samantha Zottola +5

Risk assessment instrument (RAI) datasets, particularly ProPublica's COMPAS dataset, are commonly used in algorithmic fairness papers due to benchmarking practices of comparing alg…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.