activity
20172026
most citedFlipTest: Fairness Testing via Optimal Transport

58 citations · 124 across the 8 of their papers we have counts for

collaborators

8 papers

cs.DB2026

Evergreen: Efficient Claim Verification for Semantic Aggregates

Alexander W. Lee, Benjamin Han, Shayak Sen +3

With recent semantic query processing engines, semantic aggregation has become a primitive operator, enabling the reduction of a relation into a natural language aggregate using an…

cs.LG2022★ 2 cited

Black-Box Audits for Group Distribution Shifts

Marc Juarez, Samuel Yeom, Matt Fredrikson

When a model informs decisions about people, distribution shifts can create undue disparities. However, it is hard for external entities to check for distribution shift, as the mod…

cs.LG2020★ 1 cited

Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness

Samuel Yeom, Matt Fredrikson

We turn the definition of individual fairness on its head---rather than ascertaining the fairness of a model given a predetermined metric, we find a metric for a given model that s…

cs.LG2019★ 15 cited

Learning Fair Representations for Kernel Models

Zilong Tan, Samuel Yeom, Matt Fredrikson +1

Fair representations are a powerful tool for establishing criteria like statistical parity, proxy non-discrimination, and equality of opportunity in learned models. Existing techni…

cs.LG2019★ 58 cited

FlipTest: Fairness Testing via Optimal Transport

Emily Black, Samuel Yeom, Matt Fredrikson

We present FlipTest, a black-box technique for uncovering discrimination in classifiers. FlipTest is motivated by the intuitive question: had an individual been of a different prot…

cs.LG2018★ 15 cited

Hunting for Discriminatory Proxies in Linear Regression Models

Samuel Yeom, Anupam Datta, Matt Fredrikson

A machine learning model may exhibit discrimination when used to make decisions involving people. One potential cause for such outcomes is that the model uses a statistical proxy f…