5 citations · 7 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 2 cited
Interpretable Assessment of Fairness During Model Evaluation
Amir Sepehri, Cyrus DiCiccio
For companies developing products or algorithms, it is important to understand the potential effects not only globally, but also on sub-populations of users. In particular, it is i…
stat.AP2020
Evaluating Fairness Using Permutation Tests
Cyrus DiCiccio, Sriram Vasudevan, Kinjal Basu +2
Machine learning models are central to people's lives and impact society in ways as fundamental as determining how people access information. The gravity of these models imparts a…
cs.AI2020★ 5 cited
A Framework for Fairness in Two-Sided Marketplaces
Kinjal Basu, Cyrus DiCiccio, Heloise Logan +1
Many interesting problems in the Internet industry can be framed as a two-sided marketplace problem. Examples include search applications and recommender systems showing people, jo…