123 citations · 366 across the 30 of their papers we have counts for
36 papers
The Misuse of AUC: What High Impact Risk Assessment Gets Wrong
Kweku Kwegyir-Aggrey, Marissa Gerchick, Malika Mohan +2
When determining which machine learning model best performs some high impact risk assessment task, practitioners commonly use the Area under the Curve (AUC) to defend and validate…
Disentangling Influence: Using Disentangled Representations to Audit Model Predictions
Charles T. Marx, Richard Lanas Phillips, Sorelle A. Friedler +2
Motivated by the need to audit complex and black box models, there has been extensive research on quantifying how data features influence model predictions. Feature influence can b…
Gaps in Information Access in Social Networks
Benjamin Fish, Ashkan Bashardoust, danah boyd +3
The study of influence maximization in social networks has largely ignored disparate effects these algorithms might have on the individuals contained in the social network. Individ…
Fairness in representation: quantifying stereotyping as a representational harm
Mohsen Abbasi, Sorelle A. Friedler, Carlos Scheidegger +1
While harms of allocation have been increasingly studied as part of the subfield of algorithmic fairness, harms of representation have received considerably less attention. In this…
Sublinear Algorithms for MAXCUT and Correlation Clustering
Aditya Bhaskara, Samira Daruki, Suresh Venkatasubramanian
We study sublinear algorithms for two fundamental graph problems, MAXCUT and correlation clustering. Our focus is on constructing core-sets as well as developing streaming algorith…
A comparative study of fairness-enhancing interventions in machine learning
Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian +3
Computers are increasingly used to make decisions that have significant impact in people's lives. Often, these predictions can affect different population subgroups disproportionat…